BibSLEIGH — mining tag

mining

mining

Tag #mining

2030 papers:

PADL-2020-ShakerinG #induction #using: Whitebox Induction of Default Rules Using High-Utility Itemset Mining (FS, GG), pp. 168–176.
PADL-2020-TarauB #graph #interactive #prolog: Interactive Text Graph Mining with a Prolog-based Dialog Engine (PT, EB0), pp. 3–19.
EDM-2019-AulckNVBW #predict: Mining University Registrar Records to Predict First-Year Undergraduate Attrition (LSA, DN, NV, JB, JW).
EDM-2019-YahyaMO #data mining #education #effectiveness #novel #source code #using: A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs (AAY, FAM, AO).
ICPC-2019-MashhadiH #algorithm #empirical #specification: An empirical study on practicality of specification mining algorithms on a real-world application (MJM, HH), pp. 65–69.
ICPC-2019-SilvaR0SPM #programming #recommendation: Recommending comprehensive solutions for programming tasks by mining crowd knowledge (RFGdS, CKR, MMR0, KAS, KVRP, MdAM), pp. 358–368.
MSR-2019-CamposSMB0 #javascript: Mining rule violations in JavaScript code snippets (UC, GS, JPM, RB, GP0), pp. 195–199.
MSR-2019-ChatterjeeDPAK #case study #re-engineering #tool support: Exploratory study of slack Q&A chats as a mining source for software engineering tools (PC, KD, LLP, VA, NAK), pp. 490–501.
MSR-2019-DiamantopoulosS #evolution #stack overflow #towards: Towards mining answer edits to extract evolution patterns in stack overflow (TD, MIS, ALS), pp. 215–219.
MSR-2019-GaoKLBK #android: Negative results on mining crypto-API usage rules in Android apps (JG, PK, LL0, TFB, JK), pp. 388–398.
MSR-2019-GoteSS #git #named #network #repository #scalability: git2net: mining time-stamped co-editing networks from large git repositories (CG, IS, FS), pp. 433–444.
MSR-2019-KolovosNBMP #distributed #framework #named #repository: Crossflow: a framework for distributed mining of software repositories (DSK, PN, KB, NM, RFP), pp. 155–159.
MSR-2019-KovalenkoBBB #library #named: PathMiner: a library for mining of path-based representations of code (VK, EB, TB, AB), pp. 13–17.
MSR-2019-MaBAZM #framework #open source: World of code: an infrastructure for mining the universe of open source VCS data (YM, CB, SA, RZ, AM), pp. 143–154.
MSR-2019-MatalongaCC0PSF #android #energy: GreenHub farmer: real-world data for Android energy mining (HM, BC, FC, MC0, RP, SMdS, JPF), pp. 171–175.
SANER-2019-AshrafME #dependence #developer #interactive: Mining Cross-Task Artifact Dependencies from Developer Interactions (UA, CMD, AE), pp. 186–196.
SANER-2019-PachecoBMNMR #framework #recommendation #scala: Mining Scala Framework Extensions for Recommendation Patterns (YP, JDB, TM, DDN, WDM, CDR), pp. 514–523.
SANER-2019-SunBBS #documentation #specification #using: Mining Specifications from Documentation using a Crowd (PS, CB, IB, KTS), pp. 275–286.
SEFM-2019-Aalst #convergence #process: Object-Centric Process Mining: Dealing with Divergence and Convergence in Event Data (WMPvdA), pp. 3–25.
CoG-2019-YangHZYC0ML #game studies #online #predict: Mining Player In-game Time Spending Regularity for Churn Prediction in Free Online Games (WY, TH, JZ, GY, JC, LC0, SM, YEL), pp. 1–8.
CIKM-2019-ChelliahZS #multi #overview #recommendation: Recommendation for Multi-stakeholders and through Neural Review Mining (MC, YZ, SS), pp. 2979–2981.
CIKM-2019-DuanZYZLWWZS0 #learning #multi #summary: Legal Summarization for Multi-role Debate Dialogue via Controversy Focus Mining and Multi-task Learning (XD, YZ, LY, XZ, XL, TW, RW, QZ, CS, FW0), pp. 1361–1370.
CIKM-2019-KangT #named #network: N2N: Network Derivative Mining (JK, HT), pp. 861–870.
CIKM-2019-KawabataMS #automation #data type: Automatic Sequential Pattern Mining in Data Streams (KK, YM, YS), pp. 1733–1742.
CIKM-2019-PaikXL: DTMBIO 2019: The Thirteenth International Workshop on Data and Text Mining in Biomedical Informatics (HP, RX, DL), pp. 2985–2987.
CIKM-2019-WangCCCHHLC #bound #interactive #mobile #named #process #visualisation: TraVis: An Interactive Visualization System for Mining Inbound Traveler Activities by Leveraging Mobile Ad Request Data (PXW, HC, WQC, CCC, YHH, THH, YL, CHC), pp. 2881–2884.
CIKM-2019-WangJLHMD #community #network #sentiment #social: Emotional Contagion-Based Social Sentiment Mining in Social Networks by Introducing Network Communities (XW, DJ, ML, DH, KM, JD), pp. 1763–1772.
KDD-2019-Chen0 #data mining #machine learning #optimisation #order #robust: Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning (PYC, SL0), pp. 3233–3234.
KDD-2019-Chien #comprehension #learning: Deep Bayesian Mining, Learning and Understanding (JTC), pp. 3197–3198.
KDD-2019-LiuGNWXLLX #comprehension #concept #documentation #query: A User-Centered Concept Mining System for Query and Document Understanding at Tencent (BL, WG, DN, CW, SX, JL, KL, YX), pp. 1831–1841.
KDD-2019-LiX #data mining #named #privacy #scalability: PrivPy: General and Scalable Privacy-Preserving Data Mining (YL, WX), pp. 1299–1307.
KDD-2019-LuSPHM: Investigate Transitions into Drug Addiction through Text Mining of Reddit Data (JL, SS, RP, MAH, GM), pp. 2367–2375.
KDD-2019-PellegrinaRV #named #testing: SPuManTE: Significant Pattern Mining with Unconditional Testing (LP, MR, FV), pp. 1528–1538.
KDD-2019-PellegrinaRV19a #statistics #testing: Hypothesis Testing and Statistically-sound Pattern Mining (LP, MR, FV), pp. 3215–3216.
KDD-2019-RozenshteinG #network: Mining Temporal Networks (PR, AG), pp. 3225–3226.
KDD-2019-ShangSL0 #network: Constructing and Mining Heterogeneous Information Networks from Massive Text (JS, JS, LL, JH0), pp. 3191–3192.
KDD-2019-SpiliopoulouP #comprehension: Mining and Model Understanding on Medical Data (MS, PP), pp. 3223–3224.
KDD-2019-VreekenY #data mining #theory and practice: Modern MDL meets Data Mining Insights, Theory, and Practice (JV, KY), pp. 3229–3230.
KDD-2019-XiaoS #data mining #development #named #tutorial: Tutorial: Data Mining Methods for Drug Discovery and Development (CX, JS), pp. 3195–3196.
KDD-2019-YoshidaTK #graph #learning #metric: Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining (TY, IT, MK), pp. 1026–1036.
KDD-2019-ZarrinkalamFB #social: Social User Interest Mining: Methods and Applications (FZ, HF, EB), pp. 3235–3236.
KDD-2019-ZhaCLY #algorithm #roadmap: Mining Algorithm Roadmap in Scientific Publications (HZ, WC, KL, XY), pp. 1083–1092.
KDD-2019-ZhaoGS #keyword #named: Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering (JZ, ZG, HS), pp. 1389–1398.
ASE-2019-NamHMMV #api #identification #named #problem #usability: MARBLE: Mining for Boilerplate Code to Identify API Usability Problems (DN, AH, AM, BAM, BV), pp. 615–627.
ESEC-FSE-2019-OlssonF #ecosystem #industrial #risk management: Risks and assets: a qualitative study of a software ecosystem in the mining industry (TO, UF), pp. 895–904.
ICSE-2019-0008ZBPL: Pattern-based mining of opinions in Q&A websites (BL0, FZ, GB, MDP, ML), pp. 548–559.
ICSE-2019-AmarR #debugging #fault #locality #predict: Mining historical test logs to predict bugs and localize faults in the test logs (AA, PCR), pp. 140–151.
ICSE-2019-DmeiriTWBLDVR #dataset #named: BugSwarm: mining and continuously growing a dataset of reproducible failures and fixes (DAT, ND, YW, AB, YCL, PTD, BV, CRG), pp. 339–349.
ICSE-2019-NguyenNDNTH #fine-grained #graph #semantics: Graph-based mining of in-the-wild, fine-grained, semantic code change patterns (HAN, TNN, DD, SN, HT, MH), pp. 819–830.
ICSE-2019-NguyenRRODP #api #named #recommendation: FOCUS: a recommender system for mining API function calls and usage patterns (PTN, JDR, DDR, LO, TD, MDP), pp. 1050–1060.
ICSE-2019-YatishJTT #fault #question: Mining software defects: should we consider affected releases? (SY, JJ, PT, CT), pp. 654–665.
CASE-2019-Dagnino #data mining #process: Data Mining Methods to Analyze Alarm Logs in IoT Process Control Systems (AD), pp. 323–330.
CASE-2019-TheisMD #logic #process #programmable: Process Mining of Programmable Logic Controllers: Input/Output Event Logs (JT, IM, HD), pp. 216–221.
EDM-2018-AlsaadBGSZ #concept #dependence #graph: Mining MOOC Lecture Transcripts to Construct Concept Dependency Graphs (FA, AB, CG, HS, CZ).
EDM-2018-BoubekkiJB: Mining User Trajectories in Electronic Text Books (AB, SJ, UB).
EDM-2018-ChenLG #data mining #education #online: Re-designing the Structure of Online Courses to Empower Educational Data Mining (ZC, SL, GG).
EDM-2018-ChopraG #learning: Job Description Mining to Understand Work-Integrated Learning (SC, LG).
EDM-2018-ChopraGKMG #approach #difference #gender: Gender Differences in Undergraduate Engineering Applicants: A Text Mining Approach (SC, HG, AK, MM, LG).
EDM-2018-Perez-LemoncheD #concept #student: Mining Student Misconceptions from Pre- and Post-Testing Data (ÁPL, BD, DEP).
ICPC-2018-Ko #challenge #comprehension: Mining the mind, minding the mine: grand challenges in comprehension and mining (AJK0), p. 1.
ICSME-2018-LiLSXPLZ #api #graph: Improving API Caveats Accessibility by Mining API Caveats Knowledge Graph (HL, SL, JS, ZX, XP0, ML, XZ), pp. 183–193.
ICSME-2018-SaidQK #embedded #on the #state machine: On State Machine Mining from Embedded Control Software (WS, JQ, RK), pp. 138–148.
MSR-2018-JoonbakhshS #ide #interactive #metric #process: Mining and extraction of personal software process measures through IDE interaction logs (AJ, AS), pp. 78–81.
MSR-2018-Ko #challenge #comprehension: Mining the mind, minding the mine: grand challenges in comprehension and mining (AJK0), p. 118.
MSR-2018-MajumderBBFM08 #case study #learning #performance #stack overflow: 500+ times faster than deep learning: a case study exploring faster methods for text mining stackoverflow (SM, NB, KB, WF0, TM), pp. 554–563.
MSR-2018-Russo #profiling: Profiling call changes via motif mining (BR), pp. 203–214.
SANER-2018-BaoLL #question: Mining sandboxes: Are we there yet? (LB, TDBL, DL0), pp. 445–455.
SANER-2018-ChatleyJ #automation #code review #named #overview #repository: Diggit: Automated code review via software repository mining (RC, LJ), pp. 567–571.
SANER-2018-HossainVHKJS #api: Mining accurate message formats for service APIs (MAH, SV, JH0, MAK, JJ, JGS), pp. 266–276.
SANER-2018-LeemansAB18a #analysis #process #scalability #statechart #using: The Statechart Workbench: Enabling scalable software event log analysis using process mining (ML, WMPvdA, MGJvdB), pp. 502–506.
SANER-2018-LiuZ #program repair #stack overflow: Mining stackoverflow for program repair (XL, HZ), pp. 118–129.
SANER-2018-MoverSOC #corpus #framework #graph: Mining framework usage graphs from app corpora (SM, SS0, RBPO, BYEC), pp. 277–289.
SANER-2018-Salem #agile #identification #named: GoldRusher: A miner for rapid identification of hidden code (AS), pp. 517–521.
AIIDE-2018-YoonAHK #architecture #design: Design Mining for Minecraft Architecture (EY, EA, BH, RAK), pp. 250–256.
CIKM-2018-AslayNMG #evolution #graph: Mining Frequent Patterns in Evolving Graphs (ÇA, MAUN, GDFM, AG), pp. 923–932.
CIKM-2018-GalimbertiBBCG #network: Mining (maximal) Span-cores from Temporal Networks (EG, AB, FB, CC, FG), pp. 107–116.
CIKM-2018-KweeCPL #lifecycle #named #using #visualisation: Traffic-Cascade: Mining and Visualizing Lifecycles of Traffic Congestion Events Using Public Bus Trajectories (ATK, MFC, PKP, EPL), pp. 1955–1958.
CIKM-2018-LeiXWP #behaviour #named: CAPatternMiner: Mining Ship Collision Avoidance Behavior from AIS Trajectory Data (PRL, LPX, YTW, WCP), pp. 1875–1878.
CIKM-2018-MundraKSM #comprehension: Mining & Summarizing E-petitions for Enhanced Understanding of Public Opinion (SM, SK, MS, SM), pp. 1695–1698.
CIKM-2018-VazirgiannisMN #graph #information retrieval #named: GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs (MV, FDM, GN), pp. 2295–2296.
CIKM-2018-WangYWJZZW #data mining #graph #named #scalability: AceKG: A Large-scale Knowledge Graph for Academic Data Mining (RW, YY, JW, YJ, YZ, WZ0, XW), pp. 1487–1490.
ECIR-2018-GharebaghRN #agile #approach #novel: T-Shaped Mining: A Novel Approach to Talent Finding for Agile Software Teams (SSG, PR, MN), pp. 411–423.
ECIR-2018-TrikhaZB #detection #topic: Topic-Association Mining for User Interest Detection (AKT, FZ, EB), pp. 665–671.
ICPR-2018-BicegoLDGA #modelling #topic #using: Mining NMR Spectroscopy Using Topic Models (MB, PL, MD, FG, MA), pp. 3784–3789.
ICPR-2018-LiuZWWZ #identification #multi: Identification of Hypertension by Mining Class Association Rules from Multi-dimensional Features (FL0, XZ, ZW, TW, YZ), pp. 3114–3119.
ICPR-2018-QieG00W #correlation: Improved Correlation Filter Tracking with Hard Negative Mining (CQ, GG, YY0, LZ0, HW), pp. 1646–1651.
KDD-2018-DuT #equation #graph #named #performance: FASTEN: Fast Sylvester Equation Solver for Graph Mining (BD, HT), pp. 1339–1347.
KDD-2018-PeakeW #modelling #recommendation: Explanation Mining: Post Hoc Interpretability of Latent Factor Models for Recommendation Systems (GP, JW), pp. 2060–2069.
KDD-2018-PellegrinaV #mutation testing #performance #permutation #testing: Efficient Mining of the Most Significant Patterns with Permutation Testing (LP, FV), pp. 2070–2079.
KDD-2018-RiondatoV #named #pseudo: MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension (MR, FV), pp. 2130–2139.
PLATEAU-2018-Lemay #comprehension #git #java #repository #usability: Understanding Java Usability by Mining GitHub Repositories (MJL), p. 9.
ASE-2018-KovalenkoPB #branch #question: Mining file histories: should we consider branches? (VK, FP, AB), pp. 202–213.
ASE-2018-Krismayer #automation #constraints #monitoring: Automatic mining of constraints for monitoring systems of systems (TK), pp. 924–927.
ESEC-FSE-2018-DeFreez #specification: Mining error-handling specifications for systems software (DD), pp. 983–985.
ESEC-FSE-2018-DeFreezTR #specification: Path-based function embedding and its application to error-handling specification mining (DD, AVT, CRG), pp. 423–433.
ESEC-FSE-2018-LeB0 #named #network #specification #using: DSM: a specification mining tool using recurrent neural network based language model (TDBL, LB, DL0), pp. 896–899.
ESEC-FSE-2018-SpadiniAB #framework #named #python #repository: PyDriller: Python framework for mining software repositories (DS, MFA, AB), pp. 908–911.
ICSE-2018-YuJ #data flow #dependence: Dataflow tunneling: mining inter-request data dependencies for request-based applications (XY, GJ), pp. 586–597.
ICST-2018-PradhanW00L #multi #named #testing #using: REMAP: Using Rule Mining and Multi-objective Search for Dynamic Test Case Prioritization (DP, SW0, SA0, TY0, ML), pp. 46–57.
JCDL-2017-SaggionR #data mining: Scholarly Data Mining: Making Sense of Scientific Literature (HS, FR), pp. 346–347.
EDM-2017-BeckCB #data mining #education #learning: Workshop proposal: deep learning for educational data mining (JB, MC, RSB).
EDM-2017-LynchBXG #data mining #education #graph: Graph-based Educational Data Mining (CL, TB, LX, NG).
EDM-2017-MadaioLCO #predict #using: Using Temporal Association Rule Mining to Predict Dyadic Rapport in Peer Tutoring (MAM, RL, JC, AO).
EDM-2017-ThanasuanCW #learning #student: Emerging Patterns in Student's Learning Attributes through Text Mining (KT, WC, CW).
EDM-2017-XueLC #diagrams #graph grammar: Mining Innovative Augmented Graph Grammars for Argument Diagrams through Novelty Selection (LX, CL, MC).
ICPC-2017-NguyenJQ #android #detection #repository: Android repository mining for detecting publicly accessible functions missing permission checks (HHN, LJ, TTQ), pp. 324–327.
ICSME-2017-Gupta #maintenance #predict #process #using: Improving Software Maintenance Using Process Mining and Predictive Analytics (MG0), pp. 681–686.
ICSME-2017-Li: Mining AndroZoo: A Retrospect (LL), pp. 675–680.
MSR-2017-BaoXXLL #developer #industrial #scalability: Who will leave the company?: a large-scale industry study of developer turnover by mining monthly work report (LB, ZX, XX0, DL0, SL), pp. 170–181.
MSR-2017-CorbelliniGMZL #repository #social #web #web service: Mining social web service repositories for social relationships to aid service discovery (AC, DG, CM, AZ, IL), pp. 75–79.
MSR-2017-MolderezSR: Mining change histories for unknown systematic edits (TM, RS, CDR), pp. 248–256.
MSR-2017-TiwariUNR #framework #named #platform #repository #tool support: Candoia: a platform for building and sharing mining software repositories tools as apps (NMT, GU, HAN, HR), pp. 53–63.
SANER-2017-TangL #approach #named #novel #probability #using: StiCProb: A novel feature mining approach using conditional probability (YT, HL), pp. 45–55.
CIKM-2017-CaoZL #approach #approximate #distributed #effectiveness #graph #named #scalability: PMS: an Effective Approximation Approach for Distributed Large-scale Graph Data Processing and Mining (YC, YZ, JL), pp. 1999–2002.
CIKM-2017-ChavaryEL #network #using: Summarizing Significant Changes in Network Traffic Using Contrast Pattern Mining (EAC, SME, CL), pp. 2015–2018.
CIKM-2017-HoangL #clustering #network #performance: Highly Efficient Mining of Overlapping Clusters in Signed Weighted Networks (TAH, EPL), pp. 869–878.
CIKM-2017-HuJ #data mining #modelling: IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models (XH, SJ), pp. 2565–2566.
KDD-2017-Berglund #big data: Mining Big Data in NeuroGenetics to Understand Muscular Dystrophy (AB), p. 11.
KDD-2017-BifetZFHZQHP #data type #evolution #performance: Extremely Fast Decision Tree Mining for Evolving Data Streams (AB, JZ, WF0, CH, JZ, JQ, GH0, BP), pp. 1733–1742.
KDD-2017-BlalockG #data mining #named #performance: Bolt: Accelerated Data Mining with Fast Vector Compression (DWB, JVG), pp. 727–735.
KDD-2017-GanH #data mining #framework #scalability: A Data Mining Framework for Valuing Large Portfolios of Variable Annuities (GG, JXH), pp. 1467–1475.
KDD-2017-HopeCKS: Accelerating Innovation Through Analogy Mining (TH, JC, AK, DS), pp. 235–243.
KDD-2017-KomiyamaIANM #multi #statistics #testing: Statistical Emerging Pattern Mining with Multiple Testing Correction (JK, MI, HA, TN, SiM), pp. 897–906.
KDD-2017-LabutovHBH #learning: Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites (IL, YH0, PB, DH), pp. 907–915.
KDD-2017-WangHCLYR #network: Structural Deep Brain Network Mining (SW, LH0, BC, CTL, PSY, ABR), pp. 475–484.
OOPSLA-2017-SamanthaNNR #problem #specification: Exploiting implicit beliefs to resolve sparse usage problem in usage-based specification mining (SKS, HAN, TNN, HR), p. 29.
ASE-2017-Han #question #re-engineering: Mining structures from massive text data: will it help software engineering? (JH0), p. 2.
ASE-2017-KrismayerRG #constraints #monitoring: Mining constraints for event-based monitoring in systems of systems (TK, RR, PG), pp. 826–831.
ASE-2017-LinMXXSPLZD #design #reuse: Mining implicit design templates for actionable code reuse (YL0, GM, YX, ZX, JS0, XP0, YL0, WZ, JSD), pp. 394–404.
ASE-2017-SchmidtNF #named #specification: TREM: a tool for mining timed regular specifications from system traces (LS, AN, SF), pp. 901–906.
ASE-2017-ToffolaSP #effectiveness #exclamation #generative #testing: Saying 'hi!' is not enough: mining inputs for effective test generation (LDT, CAS, MP), pp. 44–49.
ESEC-FSE-2017-HuijgensLSRGR #agile #delivery #metric #power of #predict: Strong agile metrics: mining log data to determine predictive power of software metrics for continuous delivery teams (HH, RL, DS, HR, GG, DR), pp. 866–871.
CASE-2017-LuLXZB #data mining #industrial #process #research: Research on data mining service and its application case in complex industrial process (QL, ZJL, QX, YZ, JB), pp. 1124–1129.
ICST-2017-WanLXCL #linux: Mining Sandboxes for Linux Containers (ZW, DL0, XX0, LC, SL), pp. 92–102.
WICSA-2016-YuanM #architecture #component #detection #interactive #security: Mining Software Component Interactions to Detect Security Threats at the Architectural Level (EY, SM), pp. 211–220.
JCDL-2016-BudigDK: Glyph Miner: A System for Efficiently Extracting Glyphs from Early Prints in the Context of OCR (BB, TCvD, FK), pp. 31–34.
JCDL-2016-ClarkD #research: PDFFigures 2.0: Mining Figures from Research Papers (CAC, SKD), pp. 143–152.
EDM-2016-BuffumFBWML #assessment #collaboration #embedded #learning #sequence: Mining Sequences of Gameplay for Embedded Assessment in Collaborative Learning (PSB, MF, KEB, ENW, BWM, JCL), pp. 575–576.
EDM-2016-DongKB #comparison #learning #multi #process: Comparison of Selection Criteria for Multi-Feature Hierarchical Activity Mining in Open Ended Learning Environments (YD, JSK, GB), pp. 591–592.
EDM-2016-HaoLDKK #analysis #collaboration #data mining #problem #statistics: Collaborative Problem Solving Skills versus Collaboration Outcomes: Findings from Statistical Analysis and Data Mining (JH, LL, AvD, PCK, CK), pp. 382–387.
EDM-2016-JiangG #approach #contest #graph #on the: On Competition for Undergraduate Co-op Placements: A Graph Mining Approach (YHJ, LG), pp. 394–399.
EDM-2016-McBroomJKY #behaviour #student: Mining behaviors of students in autograding submission system logs (JM, BJ, IK, KY), pp. 159–166.
EDM-2016-Penteado #assessment #data mining #estimation #scalability #semantics #using: Estimation of prerequisite skills model from large scale assessment data using semantic data mining (BEP), pp. 675–677.
EDM-2016-Rau #concept #learning #physics #social: Pattern mining uncovers social prompts of conceptual learning with physical and virtual representations (MAR), pp. 478–483.
EDM-2016-SabourinMW #data mining #education #tool support: SAS Tools for Educational Data Mining (JS, SWM, ADW), pp. 632–633.
EDM-2016-Sherzad #challenge #data mining #education: Applicability of Educational Data Mining in Afghanistan: Opportunities and Challenges (ARS), pp. 634–635.
EDM-2016-ShimadaOO #matrix: Browsing-Pattern Mining from e-Book Logs with Non-negative Matrix Factorization (AS, FO, HO), pp. 636–637.
ICPC-2016-SaiedS #api #approach: A cooperative approach for combining client-based and library-based API usage pattern mining (MAS, HAS), pp. 1–10.
MSR-2016-AhasanuzzamanAR #stack overflow: Mining duplicate questions in stack overflow (MA, MA, CKR, KAS), pp. 402–412.
MSR-2016-AveryDSG #behaviour: Externalization of software behavior by the mining of norms (DA, HKD, BTRS, AKG), pp. 223–234.
MSR-2016-BaoLXWT #android #commit #developer #empirical #how #power management: How android app developers manage power consumption?: an empirical study by mining power management commits (LB, DL0, XX0, XW0, CT), pp. 37–48.
MSR-2016-GomezRAS #android #automation #detection #performance #repository #user interface: Mining test repositories for automatic detection of UI performance regressions in Android apps (MG0, RR, BA, LS), pp. 13–24.
MSR-2016-Hassan #case study #education #experience #repository #research: Raising MSR researchers: an experience report on teaching a graduate seminar course in mining software repositories (MSR) (AEH), pp. 121–125.
MSR-2016-LuoPG #evolution #performance: Mining performance regression inducing code changes in evolving software (QL, DP, MG), pp. 25–36.
MSR-2016-MantylaADGO #detection #question: Mining valence, arousal, and dominance: possibilities for detecting burnout and productivity? (MM, BA, GD, DG, MO), pp. 247–258.
MSR-2016-MoslehiAR #documentation #on the #speech: On mining crowd-based speech documentation (PM, BA, JR), pp. 259–268.
MSR-2016-TrautschHMG #framework #platform #problem #repository: Adressing problems with external validity of repository mining studies through a smart data platform (FT, SH, PM, JG), pp. 97–108.
MSR-2016-YangKYI #code review #dataset #overview #people #process #repository: Mining the modern code review repositories: a dataset of people, process and product (XY, RGK, NY, HI), pp. 460–463.
SANER-2016-ChenGX #category theory #library #relational #word: Mining Analogical Libraries in Q&A Discussions - Incorporating Relational and Categorical Knowledge into Word Embedding (CC, SG, ZX), pp. 338–348.
SANER-2016-KarimKP #android #recommendation: Mining Android Apps to Recommend Permissions (MYK, HHK, MDP), pp. 427–437.
SANER-2016-WilleSSS #variability: Custom-Tailored Variability Mining for Block-Based Languages (DW, SS, CS0, IS), pp. 271–282.
SCAM-2016-MoonenARB #impact analysis: Exploring the Effects of History Length and Age on Mining Software Change Impact (LM, SDA, TR, DWB), pp. 207–216.
CHI-PLAY-2016-WellsCLMGS #data mining #network: Mining for Gold (and Platinum): PlayStation Network Data Mining (LW, AJCS, IJL, LM, BG, KdS), pp. 304–312.
CIG-2016-SephtonCDHS #android #predict #using: Using association rule mining to predict opponent deck content in android: Netrunner (NS, PIC, SD, VJH, NHS), pp. 1–8.
CIKM-2016-AgrawalC #data mining #predict #using: A Fatigue Strength Predictor for Steels Using Ensemble Data Mining: Steel Fatigue Strength Predictor (AA, ANC), pp. 2497–2500.
CIKM-2016-ChenDWST #data mining #recommendation: From Recommendation to Profile Inference (Rec2PI): A Value-added Service to Wi-Fi Data Mining (CC0, FD, KW0, VS0, AT), pp. 1503–1512.
CIKM-2016-HuSWXL: Mining Shopping Patterns for Divergent Urban Regions by Incorporating Mobility Data (TH, RS, YW, XX0, JL), pp. 569–578.
CIKM-2016-KimCCL: DTMBIO 2016: The Tenth International Workshop on Data and Text Mining in Biomedical Informatics (SK, JYC, VC, DL), pp. 2511–2512.
CIKM-2016-LuCL #recommendation #topic #video: Scarce Feature Topic Mining for Video Recommendation (WL0, KFLC, KL), pp. 1993–1996.
CIKM-2016-NadungodageXL #data type #framework #named: GStreamMiner: A GPU-accelerated Data Stream Mining Framework (CHN, YX, JJL), pp. 2489–2492.
CIKM-2016-ParkJLK #named: BIGtensor: Mining Billion-Scale Tensor Made Easy (NP, BJ, JL, UK), pp. 2457–2460.
CIKM-2016-SantuSZ #generative #modelling: Generative Feature Language Models for Mining Implicit Features from Customer Reviews (SKKS, PS, CZ), pp. 929–938.
CIKM-2016-ShiTWA #big data #data mining #visual notation: ACM DAVA'16: 2nd International Workshop on DAta mining meets Visual Analytics at Big Data Era (LS, HT, CW, LA), p. 2509.
CIKM-2016-WangH #database #incremental: Incremental Mining of High Utility Sequential Patterns in Incremental Databases (JZW, JLH), pp. 2341–2346.
ECIR-2016-IencoRRRT #learning #modelling #multi: MultiLingMine 2016: Modeling, Learning and Mining for Cross/Multilinguality (DI, MR, SR, PR, AT), pp. 869–873.
ECIR-2016-KimSL #topic: Subtopic Mining Based on Three-Level Hierarchical Search Intentions (SJK, JS, JHL), pp. 741–747.
ICPR-2016-AydinA #evolution #sequence: Spatiotemporal event sequence mining from evolving regions (BA, RAA), pp. 4172–4177.
ICPR-2016-Liu #hybrid #scalability: Exposing seam carving forgery under recompression attacks by hybrid large feature mining (QL), pp. 1041–1046.
KDD-2016-BanerjeeYR #approach #named #scalability: MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories (PB, PY, SR), pp. 1415–1424.
KDD-2016-FowkesS #sequence: A Subsequence Interleaving Model for Sequential Pattern Mining (JMF, CAS), pp. 835–844.
KDD-2016-GaoLZFH #crowdsourcing #reliability: Mining Reliable Information from Passively and Actively Crowdsourced Data (JG0, QL0, BZ0, WF0, JH0), pp. 2121–2122.
KDD-2016-HajianBC #algorithm #bias #data mining: Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining (SH, FB, CC0), pp. 2125–2126.
KDD-2016-Lemmerich0SHHS #behaviour: Mining Subgroups with Exceptional Transition Behavior (FL, MB0, PS, DH, AH, MS), pp. 965–974.
KDD-2016-MoralesBKGF #big data #data type: IoT Big Data Stream Mining (GDFM, AB, LK, JG, WF0), pp. 2119–2120.
KDD-2016-NakagawaSKTT #approach #performance #predict: Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining (KN, SS, MK, KT, IT), pp. 1785–1794.
KDD-2016-NandiMADB #control flow #detection #execution #graph #using: Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs (AN, AM, SA, GBD, SB), pp. 215–224.
KDD-2016-NguyenP: Text Mining in Clinical Domain: Dealing with Noise (HN, JP), pp. 549–558.
KDD-2016-PrakashR #algorithm #data mining #modelling: Leveraging Propagation for Data Mining: Models, Algorithms and Applications (BAP, NR), pp. 2133–2134.
KDD-2016-WangZD #data mining #matrix #modelling: Healthcare Data Mining with Matrix Models (FW0, PZ0, JD), pp. 2137–2138.
KDD-2016-YangYWCZL: Diversified Temporal Subgraph Pattern Mining (YY, DY0, HW, JC, SZ, JCSL), pp. 1965–1974.
SKY-2016-Speicher16a #source code: Mining Source Code Regularities with FCA and Association Rules (DS), pp. 75–77.
MoDELS-2016-HebigHCRF #git #open source #uml: The quest for open source projects that use UML: mining GitHub (RH, THQ, MRVC, GR, MAF), pp. 173–183.
MoDELS-2016-KalenkovaALR #modelling #process #using: Process mining using BPMN: relating event logs and process models (AAK, WMPvdA, IAL, VAR), p. 123.
ASE-2016-ChengPJZYZ #detection: Mining revision histories to detect cross-language clones without intermediates (XC, ZP, LJ, HZ, HY, JZ), pp. 696–701.
ASE-2016-Greene0 #developer #identification #named #open source: CVExplorer: identifying candidate developers by mining and exploring their open source contributions (GJG, BF), pp. 804–809.
ASE-2016-HoscheleZ: Mining input grammars from dynamic taints (MH, AZ), pp. 720–725.
ASE-2016-MoonenABR #guidelines #recommendation #using: Practical guidelines for change recommendation using association rule mining (LM, SDA, DB, TR), pp. 732–743.
FSE-2016-BruninkR #performance #specification: Mining performance specifications (MB, DSR), pp. 39–49.
FSE-2016-FowkesS #api #git #probability: Parameter-free probabilistic API mining across GitHub (JMF, CAS), pp. 254–265.
ICSE-2016-JamrozikSZ: Mining sandboxes (KJ, PvSR, AZ), pp. 37–48.
ICSE-2016-LiangBZSYC #debugging #named: AntMiner: mining more bugs by reducing noise interference (BL0, PB, YZ, WS, WY, YC0), pp. 333–344.
ICSE-2016-LuLLXMH0F #android #named #scalability: PRADA: prioritizing android devices for apps by mining large-scale usage data (XL, XL, HL, TX0, QM, DH, GH0, FF0), pp. 3–13.
CASE-2016-ChengZWCJL #case study #data mining #energy #fault #using: Case studies of fault diagnosis and energy saving in buildings using data mining techniques (ZC, QZ, FW, ZC, YJ, YL), pp. 646–651.
HT-2015-Orellana-Rodriguez #recommendation: Mining Affective Context in Short Films for Emotion-Aware Recommendation (COR, EDA, WN), pp. 185–194.
SIGMOD-2015-AmsterdamerKM #interface #named #natural language: NL2CM: A Natural Language Interface to Crowd Mining (YA, AK, TM), pp. 1433–1438.
SIGMOD-2015-BeedkarG #named #scalability #sequence: LASH: Large-Scale Sequence Mining with Hierarchies (KB, RG), pp. 491–503.
SIGMOD-2015-GurukarRR #approach #commit #communication #named #network #scalability: COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks (SG, SR, BR), pp. 475–489.
SIGMOD-2015-LiuSWRH #corpus #quality: Mining Quality Phrases from Massive Text Corpora (JL, JS, CW, XR, JH), pp. 1729–1744.
SIGMOD-2015-SakuraiMF: Mining and Forecasting of Big Time-series Data (YS, YM, CF), pp. 919–922.
SIGMOD-2015-TrummerHLSG #web: Mining Subjective Properties on the Web (IT, AYH, HL, SS, RG), pp. 1745–1760.
VLDB-2015-DoLW: Mining Revenue-Maximizing Bundling Configuration (LD, HWL, KW), pp. 593–604.
VLDB-2015-KoutraJNF #graph #interactive #named #scalability #visualisation: Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool (DK, DJ, YN, CF), pp. 1924–1935.
EDM-2015-AgnihotriAMRE #student: Mining Login Data For Actionable Student Insight (LA, AA, SM, MR, AE), pp. 472–475.
EDM-2015-BravoRLP #data mining #education #online #tool support: Exploring the Influence of ICT in online Education Through Data Mining Tools (JB, SJR, JML, SP), pp. 540–543.
EDM-2015-ChenWL #probability: Discovering Prerequisite Structure of Skills through Probabilistic Association Rules Mining (YC0, PHW, JML), pp. 117–124.
EDM-2015-CrossleyMBWPBB #data mining #education #online: Language to Completion: Success in an Educational Data Mining Massive Open Online Class (SAC, DSM, RSB, YW, LP, TB, YB), pp. 388–391.
EDM-2015-CuadrosGRGZO #data mining #education: Educational Data Mining in an Open-Ended Remote Laboratory on Electric Circuits. Goals and Preliminary Results (JC, LGS, SR, MLG, JGZ, PO), pp. 578–579.
EDM-2015-Olivares-Rodriguez #learning #student #word: Learning the Creative Potential of Students by Mining a Word Association Task (COR, MG), pp. 400–403.
EDM-2015-RiddleBGMCCP #identification: Mining a Written Values Affirmation Intervention to Identify the Unique Linguistic Features of Stigmatized Groups (TR, SB, WG, SM, GC, JC, VPV), pp. 274–281.
EDM-2015-SabourinKFM #data mining #education #industrial #privacy #student: Student Privacy and Educational Data Mining: Perspectives from Industry (JS, LK, CF, SWM), pp. 164–170.
EDM-2015-Tibbles #data mining #learning: Exploring the Impact of Spacing in Mathematics Learning through Data Mining (RT), pp. 590–591.
ICSME-2015-NagyC #fault #query #sql #stack overflow: Mining Stack Overflow for discovering error patterns in SQL queries (CN, AC), pp. 516–520.
ICSME-2015-ValeM #architecture #dynamic analysis #named #using: Keecle: Mining key architecturally relevant classes using dynamic analysis (LdNV, MdAM), pp. 566–570.
ICSME-2015-WangPV #corpus #scalability: Developing a model of loop actions by mining loop characteristics from a large code corpus (XW, LLP, KVS), pp. 51–60.
MSR-2015-AbateCGFTZ #component #repository: Mining Component Repositories for Installability Issues (PA, RDC, LG, FLF, RT, SZ), pp. 24–33.
MSR-2015-CalefatoLMN #stack overflow: Mining Successful Answers in Stack Overflow (FC, FL, MCM, NN), pp. 430–433.
MSR-2015-ChowdhuryH #stack overflow #topic: Mining StackOverflow to Filter Out Off-Topic IRC Discussion (SAC, AH), pp. 422–425.
MSR-2015-Marinescu: Confessions of a Worldly Software Miner (RM), p. 1.
MSR-2015-MartinHJSZ #problem: The App Sampling Problem for App Store Mining (WM, MH, YJ, FS, YZ), pp. 123–133.
MSR-2015-MouraPEC #commit #energy: Mining Energy-Aware Commits (IM, GP, FE, FC), pp. 56–67.
MSR-2015-PonzanelliML #development #semistructured data: Summarizing Complex Development Artifacts by Mining Heterogeneous Data (LP, AM, ML), pp. 401–405.
MSR-2015-VasquezWBMP #android #execution #generative: Mining Android App Usages for Generating Actionable GUI-Based Execution Scenarios (MLV, MW, CBC, KM, DP), pp. 111–122.
SANER-2015-LeL #metric #rule-based #specification: Beyond support and confidence: Exploring interestingness measures for rule-based specification mining (TDBL, DL), pp. 331–340.
SANER-2015-MondalRS #named #refactoring: SPCP-Miner: A tool for mining code clones that are important for refactoring or tracking (MM, CKR, KAS), pp. 484–488.
SANER-2015-SaiedBAS #api #multi: Mining Multi-level API Usage Patterns (MAS, OB, HA, HAS), pp. 23–32.
SANER-2015-WongLT #automation #generative #named #source code: CloCom: Mining existing source code for automatic comment generation (EW, TL, LT), pp. 380–389.
SCAM-2015-PanditaJSW #api #using: Discovering likely mappings between APIs using text mining (RP, RPJ, SDS, LAW), pp. 231–240.
LATA-2015-ChoHK: Frequent Pattern Mining with Non-overlapping Inversions (DJC, YSH, HK), pp. 121–132.
CIG-2015-DobreL #game studies #learning #online: Online learning and mining human play in complex games (MSD, AL), pp. 60–67.
CIG-2015-WehrD #game studies: Mining game logs to create a playbook for unit AIs (DW, JD), pp. 391–398.
CHI-2015-CaoLLT #graph #interactive #multi #named #visual notation: g-Miner: Interactive Visual Group Mining on Multivariate Graphs (NC, YRL, LL, HT), pp. 279–288.
CHI-2015-SadauskasBA #design #framework #platform #social #social media: Mining Memories: Designing a Platform to Support Social Media Based Writing (JS, DB, RKA), pp. 3691–3700.
CAiSE-2015-EckLLA #named #process: PM²: A Process Mining Project Methodology (MLvE, XL, SJJL, WMPvdA), pp. 297–313.
ICEIS-v1-2015-Aghbari #big data #challenge: Mining Big Data — Challenges and Opportunities (ZAA), pp. 379–384.
ICEIS-v1-2015-Castanon-PugaSG #algorithm #data mining #fuzzy #logic #mobile #using: Hybrid-Intelligent Mobile Indoor Location Using Wi-Fi Signals — Location Method Using Data Mining Algorithms and Type-2 Fuzzy Logic Systems (MCP, ASC, CGP, GLS, MFP, EAT), pp. 609–615.
ICEIS-v1-2015-SunB #classification #process: Function-based Case Classification for Improving Business Process Mining (YS, BB), pp. 251–258.
ICEIS-v2-2015-AngioniCT #collaboration: Evaluating Potential Improvements of Collaborative Filtering with Opinion Mining (MA, MLC, FT), pp. 656–661.
ICEIS-v2-2015-FariasNOCM #case study #commit #email #repository: Analyzing Distributions of Emails and Commits from OSS Contributors through Mining Software Repositories — An Exploratory Study (MAdFF, RLN, PO, MCJ, MGM), pp. 303–310.
ICEIS-v2-2015-TangL #framework #product line #top-down: Top-down Feature Mining Framework for Software Product Line (YT, HL), pp. 71–81.
ICEIS-v3-2015-ThabetGG #analysis #petri net #process: Petri Net Model Cost Extension based on Process Mining — Cost Data Description and Analysis (DT, SAG, HHBG), pp. 268–275.
CIKM-2015-DuanZ #coordination #recommendation #representation: Mining Coordinated Intent Representation for Entity Search and Recommendation (HD, CZ), pp. 333–342.
CIKM-2015-ParkKPCNYR #chat #online: Mining the Minds of Customers from Online Chat Logs (KP, JK, JP, MC, JN, SY0, ER), pp. 1879–1882.
CIKM-2015-PengZLHWZ #microblog #topic: Central Topic Model for Event-oriented Topics Mining in Microblog Stream (MP, JZ, XL, JH, HW0, YZ), pp. 1611–1620.
CIKM-2015-SongHL #network #social: Mining Brokers in Dynamic Social Networks (CS, WH, MLL), pp. 523–532.
CIKM-2015-SongLV: DTMBIO 2015: International Workshop on Data and Text Mining in Biomedical Informatics (MS0, DL, KV), pp. 1941–1942.
CIKM-2015-TandonMDW #named #process: Knowlywood: Mining Activity Knowledge From Hollywood Narratives (NT, GdM, AD, GW), pp. 223–232.
CIKM-2015-WangHCWL #aspect-oriented #microblog #named #sentiment: ASEM: Mining Aspects and Sentiment of Events from Microblog (RW, WH, WC0, TW, KL), pp. 1923–1926.
ECIR-2015-Dutta #approximate #named #statistics #string #using: MIST: Top-k Approximate Sub-string Mining Using Triplet Statistical Significance (SD), pp. 284–290.
ECIR-2015-Moghaddam #analysis #fault #feedback #sentiment: Beyond Sentiment Analysis: Mining Defects and Improvements from Customer Feedback (SM), pp. 400–410.
KDD-2015-ArlorioCLLP #assessment #authentication #data mining: Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont (MA, JDC, GL, ML, LP), pp. 1671–1680.
KDD-2015-CaiTFJH #higher-order #named #performance: Facets: Fast Comprehensive Mining of Coevolving High-order Time Series (YC, HT, WF, PJ, QH), pp. 79–88.
KDD-2015-CostaYTTF #modelling #named #process #social #social media: RSC: Mining and Modeling Temporal Activity in Social Media (AFC, YY, AJMT, CTJ, CF), pp. 269–278.
KDD-2015-FeldmanNPR #online #predict: Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions (RF, ON, AP, BR), pp. 1779–1788.
KDD-2015-GreenCCMPM: Mining Administrative Data to Spur Urban Revitalization (BG, AC, MC, RM, TP, AM), pp. 1829–1838.
KDD-2015-KimHY #named #topic: TOPTRAC: Topical Trajectory Pattern Mining (YK, JH, CY), pp. 587–596.
KDD-2015-Llinares-LopezS #mutation testing #performance #permutation #testing: Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing (FLL, MS, LP, KMB), pp. 725–734.
KDD-2015-RenEWH #approach #automation #corpus #network #recognition #type system: Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach (XR, AEK, CW, JH), pp. 2319–2320.
KDD-2015-RiondatoU: Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages (MR, EU), pp. 1005–1014.
KDD-2015-SpiliopoulouRR #tutorial: Medical Mining: KDD 2015 Tutorial (MS, PPR, EMR), p. 2325.
KDD-2015-StantonTJVCS #data-driven: Mining for Causal Relationships: A Data-Driven Study of the Islamic State (AS, AT, AJ, PV, AC, PS), pp. 2137–2146.
KDD-2015-WickerKDSBKW0 #data mining #smell: Cinema Data Mining: The Smell of Fear (JW, NK, BD, CS, EB, TK, JW, SK), pp. 1295–1304.
KDD-2015-ZhangW15a #statistics: Statistical Arbitrage Mining for Display Advertising (WZ, JW), pp. 1465–1474.
MLDM-2015-Al-SaleemAAB #education #performance #predict #student: Mining Educational Data to Predict Students’ Academic Performance (MAS, NAK, SAO, GB), pp. 403–414.
MLDM-2015-DhulekarNOY #graph #learning #predict: Seizure Prediction by Graph Mining, Transfer Learning, and Transformation Learning (ND, SN, BO, BY), pp. 32–52.
MLDM-2015-MoldovanM #data mining #learning #performance #using: Learning the Relationship Between Corporate Governance and Company Performance Using Data Mining (DM, SM), pp. 368–381.
MLDM-2015-Perner #automation #feature model #image: Automatic Cell Tracking and Kinetic Feature Description of Cell Paths for Image Mining (PP), pp. 441–451.
MLDM-2015-SalahAM #optimisation #performance #pipes and filters: Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce (SS, RA, FM), pp. 217–231.
MLDM-2015-ZidaFWLT #performance: Efficient Mining of High-Utility Sequential Rules (SZ, PFV, CWW, JCWL, VST), pp. 157–171.
SEKE-2015-ChenZWLPW #probability #specification: Mining Universal Specification Based on Probabilistic Model (DC, YZ, RW, XL, LP, WW), pp. 471–476.
SEKE-2015-ChenZWQJW #api #protocol: Extracting More Object Usage Scenarios for API Protocol Mining (DC, YZ, RW, BQ, JJ, WW), pp. 607–612.
SIGIR-2015-MaiyaVW: Mining Measured Information from Text (ASM, DV, AW), pp. 899–902.
SIGIR-2015-ReinandaMR #aspect-oriented #ranking #recommendation: Mining, Ranking and Recommending Entity Aspects (RR, EM, MdR), pp. 263–272.
SKY-2015-Allalouf #big data #library #visualisation: Big Data in the Library: Extending Modern Library Catalogues with Data Visualization, Linking and Mining (MA), pp. 74–75.
MoDELS-2015-LeemansA #distributed #modelling #process #transaction: Process mining in software systems: Discovering real-life business transactions and process models from distributed systems (ML, WMPvdA), pp. 44–53.
ASE-2015-LemieuxB #behaviour #ltl #specification #using: Investigating Program Behavior Using the Texada LTL Specifications Miner (CL, IB), pp. 870–875.
ASE-2015-LemieuxPB #ltl #specification: General LTL Specification Mining (T) (CL, DP, IB), pp. 81–92.
ASE-2015-SorboPVPCG #developer #development #email: Development Emails Content Analyzer: Intention Mining in Developer Discussions (T) (ADS, SP, CAV, MDP, GC, HCG), pp. 12–23.
ASE-2015-VuNPN #approach #keyword #mobile: Mining User Opinions in Mobile App Reviews: A Keyword-Based Approach (T) (PMV, TTN, HVP, TTN), pp. 749–759.
ICSE-v1-2015-AvdiienkoKGZARB: Mining Apps for Abnormal Usage of Sensitive Data (VA, KK, AG, AZ, SA, SR, EB), pp. 426–436.
ICSE-v1-2015-Landau #metadata: Mining the Metadata — and Its Consequences (SL), pp. 4–5.
ICSE-v2-2015-Avdiienko: Mining Patterns of Sensitive Data Usage (VA), pp. 891–894.
ICSE-v2-2015-DamSAG #repository #social: Mining Software Repositories for Social Norms (HKD, BTRS, DA, AKG), pp. 627–630.
ICSE-v2-2015-Honsel #evolution #learning #simulation #statistics: Statistical Learning and Software Mining for Agent Based Simulation of Software Evolution (VH), pp. 863–866.
ICSE-v2-2015-Lemieux #invariant: Mining Temporal Properties of Data Invariants (CL), pp. 751–753.
SAC-2015-BechetCCC #constraints #multi #sequence: Sequence mining under multiple constraints (NB, PC, TC, BC), pp. 908–914.
SAC-2015-BouaskerY #anti #constraints #correlation: Key correlation mining by simultaneous monotone and anti-monotone constraints checking (SB, SBY), pp. 851–856.
SAC-2015-Fournier-VigerZ #named #performance: FOSHU: faster on-shelf high utility itemset mining — with or without negative unit profit (PFV, SZ), pp. 857–864.
SAC-2015-MergelSS #string #visual notation: A method to support search string building in systematic literature reviews through visual text mining (GDM, MSS, TSdS), pp. 1594–1601.
SAC-2015-SantosOA #development #process: Mining software development process variations (RMSS, TCO, FBeA), pp. 1657–1660.
SAC-2015-WeberFMS #multi #process: Mining processes with multi-instantiation (IW, MF, JM, JGS), pp. 1231–1237.
SAC-2015-ZhangYLC #concept #debugging #predict #repository: Predicting severity of bug report by mining bug repository with concept profile (TZ, GY, BL, ATSC), pp. 1553–1558.
CASE-2015-MicioFMBL #automation #process #towards: RTLS-based Process Mining: Towards an automatic process diagnosis in healthcare (RM, FF, GM, PB, ML), pp. 1397–1402.
CASE-2015-NouaouriSA #data mining #predict #problem: Evidential data mining for length of stay (LOS) prediction problem (IN, AS, HA), pp. 1415–1420.
CASE-2015-ProdelAXJL #database #integer #linear #process #programming #using: Discovery of patient pathways from a national hospital database using process mining and integer linear programming (MP, VA, XX, BJ, LL), pp. 1409–1414.
CGO-2015-NagarajG #analysis #approximate #pointer #using: Approximating flow-sensitive pointer analysis using frequent itemset mining (VN, RG), pp. 225–234.
DATE-2015-FarkashHS #data mining #debugging #locality: Data mining diagnostics and bug MRIs for HW bug localization (MF, BGH, BS), pp. 79–84.
PDP-2015-AltomareCT #data mining #energy #migration #modelling #predict #virtual machine: Energy-Aware Migration of Virtual Machines Driven by Predictive Data Mining Models (AA, EC, DT), pp. 549–553.
SOSP-2015-TeixeiraFSSZA #distributed #graph #named: Arabesque: a system for distributed graph mining (CHCT, AJF, MS, GS, MJZ, AA), pp. 425–440.
ICLP-2015-Hallen #data mining #higher-order #logic #specification: Higher Order Support in Logic Specification Languages for Data Mining Applications (MvdH), pp. 330–336.
ISSTA-2015-ClappAA #data flow #named #specification: Modelgen: mining explicit information flow specifications from concrete executions (LC, SA, AA), pp. 129–140.
SAT-2015-IvriiRS #incremental #satisfiability: Mining Backbone Literals in Incremental SAT — A New Kind of Incremental Data (AI, VR, OS), pp. 88–103.
HT-2014-AgarwalS #crawling: A focused crawler for mining hate and extremism promoting videos on YouTube (SA, AS), pp. 294–296.
JCDL-2014-HarrisLZL: The anatomy of a search and mining system for digital humanities (MH, ML, DZ, DL), pp. 165–168.
JCDL-2014-LiuYGSG #approach #network #recommendation: Full-text based context-rich heterogeneous network mining approach for citation recommendation (XL, YY, CG, YS, LG), pp. 361–370.
SIGMOD-2014-AmsterdamerDMNS #named #query: OASSIS: query driven crowd mining (YA, SBD, TM, SN, AS), pp. 589–600.
SIGMOD-2014-AroraSB #graph #statistics: Mining statistically significant connected subgraphs in vertex labeled graphs (AA, MS, AB), pp. 1003–1014.
SIGMOD-2014-GalbrunM #interactive: Interactive redescription mining (EG, PM), pp. 1079–1082.
SIGMOD-2014-HanW: Mining latent entity structures from massive unstructured and interconnected data (JH, CW), pp. 1409–1410.
SIGMOD-2014-MatsubaraSF #automation #co-evolution #named #sequence: AutoPlait: automatic mining of co-evolving time sequences (YM, YS, CF), pp. 193–204.
SIGMOD-2014-YamamotoIF #approximate #data type: Resource-oriented approximation for frequent itemset mining from bursty data streams (YY, KI, SF), pp. 205–216.
VLDB-2014-AmsterdamerDMNS #ontology: Ontology Assisted Crowd Mining (YA, SBD, TM, SN, AS), pp. 1597–1600.
VLDB-2014-ElseidyASK #graph #named #scalability: GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph (ME, EA, SS, PK), pp. 517–528.
VLDB-2014-LinMRW #interactive #named: SPIRE: Supporting Parameter-Driven Interactive Rule Mining and Exploration (XL, AM, EAR, MOW), pp. 1653–1656.
VLDB-2014-WuLLH: MoveMine 2.0: Mining Object Relationships from Movement Data (FW, TKHL, ZL, JH), pp. 1613–1616.
VLDB-2014-ZhangHSLP #fine-grained #named #semantics: Splitter: Mining Fine-Grained Sequential Patterns in Semantic Trajectories (CZ, JH, LS, JL, TFLP), pp. 769–780.
VLDB-2015-El-KishkySWVH14 #corpus #scalability #topic: Scalable Topical Phrase Mining from Text Corpora (AEK, YS, CW, CRV, JH), pp. 305–316.
VLDB-2015-ThirumuruganathanRAD14: Beyond Itemsets: Mining Frequent Featuresets over Structured Items (ST, HR, SA, GD), pp. 257–268.
EDM-2014-CrossleyKVM #assessment #data mining: The Importance of Grammar and Mechanics in Writing Assessment and Instruction: Evidence from Data Mining (SAC, KK, LKV, DSM), pp. 300–303.
EDM-2014-FuentesRGV #data mining #self #student #using: Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data Mining (JF, CR, CGM, SV), pp. 327–328.
EDM-2014-MartinVAMJ #data mining #design #education #research: Microgenetic Designs for Educational Data Mining Research: Poster (TM, NFV, AA, JM, PJ), pp. 387–388.
EDM-2014-MorettiGM14a #data-driven #design #education #web: Data-Driven Curriculum Design: Mining the Web to Make Better Teaching Decisions (AM, JPGB, KM), pp. 421–422.
EDM-2014-MorrisonNSDKR #data mining #database: Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data Mining (DMM, BN, BS, VVD, CK, VR), pp. 335–336.
EDM-2014-NiraulaRSG #tutorial: Mining Gap-fill Questions from Tutorial Dialogues (NBN, VR, DS, ACG), pp. 265–268.
EDM-2014-PeckhamM #comprehension #education #framework: Mining Reading Comprehension Within Educational Objective Frameworks (TP, GM), pp. 395–396.
EDM-2014-RayBR #data mining #using: Using Data Mining to Automate ADDIE (FR, KWB, RR), pp. 429–430.
EDM-2014-SantosMP #collaboration #learning #student: Mining students' strategies to enable collaborative learning (SGS, MM, AP), pp. 397–398.
EDM-2014-ShuQF #data mining #education #experience #learning #student: Educational Data Mining and Analyzing of Student Learning Outcomes from the Perspective of Learning Experience (ZS, QFQ, LQF), pp. 359–360.
EDM-2014-SilvaA #modelling #multi #student: Mining Multi-dimensional Patterns for Student Modelling (AS0, CA), pp. 393–394.
EDM-2014-SmithWML #abstraction #named #sketching: SKETCHMINER: Mining Learner-Generated Science Drawings with Topological Abstraction (AS, ENW, BWM, JCL), pp. 288–291.
EDM-2014-SyedJG #data mining: Data mining of undergraduate course evaluations (SJS, YHJ, LG), pp. 347–348.
EDM-2014-ValeMA #clustering #education #evolution: Mining coherent evolution patterns in education through biclustering (AV, SCM, CA), pp. 391–392.
EDM-2014-YeKB #identification #learning #multi #process: Mining and Identifying Relationships Among Sequential Patterns in Multi-Feature, Hierarchical Learning Activity Data (CY, JSK, GB), pp. 389–390.
ITiCSE-2014-EricssonW #what: Mining job ads to find what skills are sought after from an employers’ perspective on IT graduates (ME, AW), p. 354.
CSMR-WCRE-2014-KashiwabaraOIHYI #recommendation #using: Recommending verbs for rename method using association rule mining (YK, YO, TI, YH, TY, KI), pp. 323–327.
CSMR-WCRE-2014-MondalRS #automation #ranking #refactoring: Automatic ranking of clones for refactoring through mining association rules (MM, CKR, KAS), pp. 114–123.
CSMR-WCRE-2014-OsmanLN #debugging: Mining frequent bug-fix code changes (HO, ML, ON), pp. 343–347.
ICPC-2014-GhafariGMT #recommendation #testing: Mining unit tests for code recommendation (MG, CG, AM, GT), pp. 142–145.
ICPC-2014-VassalloPPC #developer #named #source code: CODES: mining source code descriptions from developers discussions (CV, SP, MDP, GC), pp. 106–109.
ICSME-2014-McIntoshANH #co-evolution: Mining Co-change Information to Understand When Build Changes Are Necessary (SM, BA, MN, AEH), pp. 241–250.
ICSME-2014-YanMG #contract #evolution: Mining Software Contracts for Software Evolution (YY, MM, WGG), pp. 471–475.
ICSME-2014-ZhouTGG #classification #data mining #debugging: Combining Text Mining and Data Mining for Bug Report Classification (YZ, YT, RG, HCG), pp. 311–320.
ICSME-2014-ZhuZXJL0 #api: Mining API Usage Examples from Test Code (ZZ, YZ, BX, YJ, ZL, LZ), pp. 301–310.
MSR-2014-AndersonSD #effectiveness #testing: Improving the effectiveness of test suite through mining historical data (JA, SS, HD), pp. 142–151.
MSR-2014-BajajPM #developer #web: Mining questions asked by web developers (KB, KP, AM), pp. 112–121.
MSR-2014-GuptaSP #fault #multi #perspective #process #repository: Process mining multiple repositories for software defect resolution from control and organizational perspective (MG, AS, SP), pp. 122–131.
MSR-2014-HindleWRBCR #energy #framework #hardware #named #repository: GreenMiner: a hardware based mining software repositories software energy consumption framework (AH, AW, KR, EJB, JCC, SR), pp. 12–21.
MSR-2014-KalliamvakouGBSGD #git: The promises and perils of mining GitHub (EK, GG, KB, LS, DMG, DD), pp. 92–101.
MSR-2014-KononenkoBHG #repository: Mining modern repositories with elasticsearch (OK, OB, RH, MWG), pp. 328–331.
MSR-2014-Mockus #question #repository: Is mining software repositories data science? (AM), p. 1.
MSR-2014-PintoCL #energy: Mining questions about software energy consumption (GP, FC, YDL), pp. 22–31.
MSR-2014-PonzanelliBPOL #ide #programming #self #stack overflow: Mining StackOverflow to turn the IDE into a self-confident programming prompter (LP, GB, MDP, RO, ML), pp. 102–111.
MSR-2014-RoblesGCCI #case study #development #open source #repository: Estimating development effort in Free/Open source software projects by mining software repositories: a case study of OpenStack (GR, JMGB, CC, AC, DIC), pp. 222–231.
MSR-2014-VasquezBBOPP #android #api #empirical #energy: Mining energy-greedy API usage patterns in Android apps: an empirical study (MLV, GB, CBC, RO, MDP, DP), pp. 2–11.
MSR-2014-ZhangH #dataset #energy: A green miner’s dataset: mining the impact of software change on energy consumption (CZ, AH), pp. 400–403.
CIG-2014-GalliLL #data mining #design pattern: Applying data mining to extract design patterns from Unreal Tournament levels (LG, PLL, DL), pp. 1–8.
ICGT-2014-Bruggink #graph transformation #process #towards: Towards Process Mining with Graph Transformation Systems (HJSB), pp. 253–268.
HCI-AS-2014-Hussain #data mining: Getting the Most from CRM Systems: Data Mining in SugarCRM, Finding Important Patterns (QH), pp. 693–699.
HIMI-DE-2014-AlghamdiT #image #multimodal #retrieval #semantics #towards #using: Towards Semantic Image Retrieval Using Multimodal Fusion with Association Rules Mining (RAA, MT), pp. 407–418.
HIMI-DE-2014-TakahashiA #comparison #comprehension #difference #using: User Needs Search Using the Text Mining — From Commodity Comparison, Understanding the Difference of Users Awareness (YT, YA), pp. 461–467.
CAiSE-2014-ChanYGM #development #execution #process: Mining Event Logs to Assist the Development of Executable Process Variants (NNC, KY, WG, JM), pp. 548–563.
CAiSE-2014-EpureHDB #flexibility #process #what: What Shall I Do Next? — Intention Mining for Flexible Process Enactment (EVE, CH, RD, SB), pp. 473–487.
CAiSE-2014-FolinoGP #low level #modelling #multi #predict #process: Mining Predictive Process Models out of Low-level Multidimensional Logs (FF, MG, LP), pp. 533–547.
CAiSE-2014-SenderovichWGM #predict #process #queue: Queue Mining — Predicting Delays in Service Processes (AS, MW, AG, AM), pp. 42–57.
CAiSE-2014-SubeljBKB #process: Automatization of the Stream Mining Process (LS, ZB, MK, MB), pp. 409–423.
EDOC-2014-Aalst #enterprise #process: Process Mining as the Superglue Between Data Science and Enterprise Computing (WMPvdA), p. 1.
ICEIS-v1-2014-AmaralCRGTS #approach #data mining #framework #image: The SITSMining Framework — A Data Mining Approach for Satellite Image Time Series (BFA, DYTC, LASR, RRdVG, AJMT, EPMdS), pp. 225–232.
ICEIS-v1-2014-AntunesS #data mining #roadmap: New Trends in Knowledge Driven Data Mining (CA, AS), pp. 346–351.
ICEIS-v1-2014-DominguezAERLE #data mining #fuzzy #logic #roadmap #using: Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques (MD, JA, JGE, IMR, JMLS, MJE), pp. 325–330.
ICEIS-v1-2014-GuerineRP #data mining #metaheuristic: Extending the Hybridization of Metaheuristics with Data Mining to a Broader Domain (MG, IR, AP), pp. 395–406.
ICEIS-v1-2014-SilvaA #case study #multi: Multi-dimensional Pattern Mining — A Case Study in Healthcare (AS, CA), pp. 273–280.
ICEIS-v2-2014-HernandesTTF #analysis #using #visualisation: Using Visualization and Text Mining to Improve Qualitative Analysis (EMH, ET, ADT, SCPFF), pp. 201–208.
ICEIS-v3-2014-ThabetGG #petri net #process #towards: Towards Business Process Model Extension with Cost Perspective Based on Process Mining — Petri Net Model Case (DT, SAG, HHBG), pp. 335–342.
CIKM-2014-HsiehL: Mining and Planning Time-aware Routes from Check-in Data (HPH, CTL), pp. 481–490.
CIKM-2014-LiSWZJTLZZLTL #named: iMiner: Mining Inventory Data for Intelligent Management (LL, CS, LW, LZ, YJ, LT, HL, LZ, CZ, TL, JT, DL), pp. 2057–2059.
CIKM-2014-LiuXD #network #predict: Relationship Emergence Prediction in Heterogeneous Networks through Dynamic Frequent Subgraph Mining (YL, SX, LD), pp. 1649–1658.
CIKM-2014-MahdabiC #network #recommendation #retrieval: Query-Driven Mining of Citation Networks for Patent Citation Retrieval and Recommendation (PM, FC), pp. 1659–1668.
CIKM-2014-SondhiZ #community #knowledge base #natural language #online: Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites (PS, CZ), pp. 341–350.
CIKM-2014-WenR #behaviour #identification #online: Identifying Latent Study Habits by Mining Learner Behavior Patterns in Massive Open Online Courses (MW, CPR), pp. 1983–1986.
CIKM-2014-XuLLZCS: Latent Aspect Mining via Exploring Sparsity and Intrinsic Information (YX, TL, WL, ZZ, HC, AMCS), pp. 879–888.
CIKM-2014-ZhaoWLZ #framework #refinement #word: A Bootstrapping Based Refinement Framework for Mining Opinion Words and Targets (QZ, HW, PL, CZ), pp. 1995–1998.
ECIR-2014-MarcheggianiTE0 #aspect-oriented #multi #random: Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining (DM, OT, AE, FS), pp. 273–285.
ICPR-2014-HuLYLL #database #evaluation #multi: Multi-camera Trajectory Mining: Database and Evaluation (YH, SL, DY, ZL, SZL), pp. 4684–4689.
KDD-2014-BordesG #graph #tutorial: Constructing and mining web-scale knowledge graphs: KDD 2014 tutorial (AB, EG), p. 1967.
KDD-2014-Chen0 #big data #documentation #topic: Mining topics in documents: standing on the shoulders of big data (ZC, BL), pp. 1116–1125.
KDD-2014-ChiaS #predict #scalability: Scalable noise mining in long-term electrocardiographic time-series to predict death following heart attacks (CCC, ZS), pp. 125–134.
KDD-2014-Etzioni #data mining #future of: The battle for the future of data mining (OE), p. 1.
KDD-2014-HanWE #topic: Bringing structure to text: mining phrases, entities, topics, and hierarchies (JH, CW, AEK), p. 1968.
KDD-2014-KannanBRFLVAKKUWZ #image #web: Mining text snippets for images on the web (AK, SB, KR, JF, DL, LV, RA, AK, QK, MU, XJW, LZ), pp. 1534–1543.
KDD-2014-KateCPK #named #safety: FoodSIS: a text mining system to improve the state of food safety in singapore (KK, SC, AP, JK), pp. 1709–1718.
KDD-2014-MatsubaraSPF #automation #named: FUNNEL: automatic mining of spatially coevolving epidemics (YM, YS, WGvP, CF), pp. 105–114.
KDD-2014-SpanglerWBNDHRPCMSKLLPLDCL #automation #generative: Automated hypothesis generation based on mining scientific literature (WSS, ADW, BJB, MN, TD, PJH, SR, CRP, AC, JNM, IS, LK, AL, JJL, NP, AML, LAD, YC, OL), pp. 1877–1886.
KDD-2014-TamersoyRC #detection #graph #scalability: Guilt by association: large scale malware detection by mining file-relation graphs (AT, KAR, DHC), pp. 1524–1533.
KDD-2014-XuLGBB #modelling #similarity: Modeling professional similarity by mining professional career trajectories (YX, ZL, AG, AB, AB), pp. 1945–1954.
KDD-2014-XuWCGSKDL #data mining #delivery #network #social: Improving management of aquatic invasions by integrating shipping network, ecological, and environmental data: data mining for social good (JX, TLW, NVC, EKG, KS, RPK, JMD, DML), pp. 1699–1708.
KDD-2014-ZhengZLJXLSZLTLDLW #data mining #optimisation #process: Applying data mining techniques to address critical process optimization needs in advanced manufacturing (LZ, CZ, LL, YJ, WX, JL, CS, WZ, HL, LT, TL, BD, ML, PW), pp. 1739–1748.
KDD-2014-ZhouL #classification #multi #network: Activity-edge centric multi-label classification for mining heterogeneous information networks (YZ, LL), pp. 1276–1285.
KDD-2014-ZhuSY #analysis #network #social: Network mining and analysis for social applications (FZ, HS, XY), p. 1974.
KDD-2014-ZongWSSCHY #scalability #towards: Towards scalable critical alert mining (BZ, YW, JS, AKS, HÇ, JH, XY), pp. 1057–1066.
KDIR-2014-BarcanteJDCCS #identification #using: Identifying Drug Repositioning Targets using Text Mining (EB, MJ, FD, EC, OGC, FS), pp. 348–353.
KDIR-2014-BenhamouJSS #symmetry: Symmetry Breaking in Itemset Mining (BB, SJ, LS, YS), pp. 86–96.
KDIR-2014-DuvalCCS #twitter: Mining for Adverse Drug Events on Twitter (FD, EC, OGC, FS), pp. 354–359.
KDIR-2014-FahedBB #algorithm #predict: Episode Rules Mining Algorithm for Distant Event Prediction (LF, AB, AB), pp. 5–13.
KDIR-2014-HubwieserM #education #scalability #set: Competency Mining in Large Data Sets — Preparing Large Scale Investigations in Computer Science Education (PH, AM), pp. 315–322.
KDIR-2014-KurasEAH #data mining #security: The GDR Through the Eyes of the Stasi — Data Mining on the Secret Reports of the State Security Service of the former German Democratic Republic (CK, TE, CA, GH), pp. 360–365.
KDIR-2014-MorenoGV #data mining #recognition #using #word: Violence Recognition in Spanish Words using Data Mining (AFM, SBGB, JGVR), pp. 210–216.
KDIR-2014-PassonneauRX #detection #scalability: Company Mention Detection for Large Scale Text Mining (RJP, TR, BX), pp. 512–520.
KDIR-2014-Rinaldi #database: Text Mining Technologies for Database Curation (FR), pp. 544–548.
KDIR-2014-TisserantRP #classification #semantics #statistics #twitter: Mining Tweet Data — Statistic and Semantic Information for Political Tweet Classification (GT, MR, VP), pp. 523–529.
KEOD-2014-Aalst #people #process #what: No Knowledge Without Processes — Process Mining as a Tool to Find Out What People and Organizations Really Do (WMPvdA), pp. 1–11.
KEOD-2014-Talia #big data #data mining #distributed #information management: Big Data Mining Services and Distributed Knowledge Discovery Applications on Clouds (DT), pp. 1–5.
KMIS-2014-SelmiHA #feedback #predict: Opinion Mining for Predicting Peer Affective Feedback Helpfulness (MS, HH, EA), pp. 419–425.
KMIS-2014-VelosoPSSRA0 #data mining #modelling #predict #realtime: Real-Time Data Mining Models for Predicting Length of Stay in Intensive Care Units (RV, FP, MFS, ÁMS, FR, AA, JM), pp. 245–254.
MLDM-2014-DzubaB #music #recommendation: Mining Users Playbacks History for Music Recommendations (AD, DB), pp. 422–430.
MLDM-2014-KuleshovB #data mining #learning: Manifold Learning in Data Mining Tasks (APK, AVB), pp. 119–133.
MLDM-2014-SharmaT #social #social media: A Generalized Relationship Mining Method for Social Media Text Data (TS, DT), pp. 376–392.
MLDM-2014-WangLK #concurrent #data mining: Applications of Concurrent Sequential Patterns in Protein Data Mining (CW, JL, MK), pp. 243–257.
RecSys-2014-JannachF #data mining #modelling #process #recommendation: Recommendation-based modeling support for data mining processes (DJ, SF), pp. 337–340.
RecSys-2014-SureshRE #recommendation: Aspect-based opinion mining and recommendationsystem for restaurant reviews (VS, SR, ME), pp. 361–362.
SEKE-2014-KaurKF #low cost #using #web: Using Web Mining to Support Low Cost Historical Vehicle Traffic Analytics (CK, DK, BHF), pp. 365–370.
Onward-2014-SpasojevicLN #ecosystem #type inference: Mining the Ecosystem to Improve Type Inference for Dynamically Typed Languages (BS, ML, ON), pp. 133–142.
RE-2014-GervasiZ #traceability: Supporting traceability through affinity mining (VG, DZ), pp. 143–152.
ASE-2014-NguyenNNN #api #approach #learning #migration #statistics: Statistical learning approach for mining API usage mappings for code migration (ATN, HAN, TTN, TNN), pp. 457–468.
FSE-2014-AllamanisS #source code: Mining idioms from source code (MA, CAS), pp. 472–483.
FSE-2014-KrkaBM #automation #invariant #specification: Automatic mining of specifications from invocation traces and method invariants (IK, YB, NM), pp. 178–189.
FSE-2014-Nguyen0NR #api #corpus #scalability: Mining preconditions of APIs in large-scale code corpus (HAN, RD, TNN, HR), pp. 166–177.
FSE-2014-ZhouM: Mining micro-practices from operational data (MZ, AM), pp. 845–848.
ICSE-2014-ChenLHXZ #developer #mobile #named: AR-miner: mining informative reviews for developers from mobile app marketplace (NC, JL, SCHH, XX, BZ), pp. 767–778.
ICSE-2014-GhezziPST #behaviour #modelling #web: Mining behavior models from user-intensive web applications (CG, MP, MS, GT), pp. 277–287.
ICSE-2014-NadiBKC #analysis #constraints #empirical: Mining configuration constraints: static analyses and empirical results (SN, TB, CK, KC), pp. 140–151.
ICSE-2014-NegaraCDJ #detection #fine-grained: Mining fine-grained code changes to detect unknown change patterns (SN, MC, DD, REJ), pp. 803–813.
ICSE-2014-NguyenNNN #interprocedural #javascript #web: Mining interprocedural, data-oriented usage patterns in JavaScript web applications (HVN, HAN, ATN, TNN), pp. 791–802.
SAC-2014-EvermannA #algorithm #big data #implementation #process: Big data meets process mining: implementing the alpha algorithm with map-reduce (JE, GA), pp. 1414–1416.
SAC-2014-LiuTZ #constraints: Mining key and referential constraints enforcement patterns (KL, HBKT, HZ), pp. 850–854.
CASE-2014-ChangYLC #behaviour #towards #video: Toward mining anomalous behavior from big moving trajectories in surveillance video (CWC, MHY, CCL, KTC), pp. 1121–1126.
CASE-2014-HajovskyPOH #energy: Heat energy collection from thermally active mining dump Hedvika (RH, MP, SO, JH), pp. 44–49.
CASE-2014-HungCYDYW #behaviour #data mining: Data mining for analysing kiosk usage behavior patterns (YSH, KLBC, CTY, GFD, YHY, NCW), pp. 1115–1120.
DAC-2014-LinWC #data mining #design #logic #named #power management #synthesis: C-Mine: Data Mining of Logic Common Cases for Low Power Synthesis of Better-Than-Worst-Case Designs (CHL, LW, DC), p. 6.
DAC-2014-WangA #constraints #data mining: Data Mining In EDA — Basic Principles, Promises, and Constraints (LCW, MSA), p. 6.
DATE-2014-FerentD #comparison #novel #synthesis #using: Novel circuit topology synthesis method using circuit feature mining and symbolic comparison (CF, AD), pp. 1–4.
DATE-2014-LagraaTP #data mining #scalability #simulation #using: Scalability bottlenecks discovery in MPSoC platforms using data mining on simulation traces (SL, AT, FP), pp. 1–6.
FASE-2014-SadeghiEM #analysis #repository #security: Mining the Categorized Software Repositories to Improve the Analysis of Security Vulnerabilities (AS, NE, SM), pp. 155–169.
ISSTA-2014-SchurRZ #modelling #multi #named #web: ProCrawl: mining test models from multi-user web applications (MS, AR, AZ), pp. 413–416.
ISSTA-2014-ZuoKS #debugging #performance: Efficient predicated bug signature mining via hierarchical instrumentation (ZZ, SCK, CS), pp. 215–224.
CBSE-2013-KarveS #component #online #towards: Towards mining informal online data to guide component-reuse decisions (SK, CS), pp. 65–74.
JCDL-2013-AfiontziKPSTP #evaluation #library #semantics: Charting the digital library evaluation domain with a semantically enhanced mining methodology (EA, GK, LP, MS, GT, CP), pp. 125–134.
PODS-2013-KimelfeldK #complexity: The complexity of mining maximal frequent subgraphs (BK, PGK), pp. 13–24.
SIGMOD-2013-AchtertKSZ #3d #coordination #data mining #interactive: Interactive data mining with 3D-parallel-coordinate-trees (EA, HPK, ES, AZ), pp. 1009–1012.
SIGMOD-2013-AmsterdamerGMS: Crowd mining (YA, YG, TM, PS), pp. 241–252.
SIGMOD-2013-GuilleFHZ #analysis #framework #named #open source #platform #social: SONDY: an open source platform for social dynamics mining and analysis (AG, CF, HH, DAZ), pp. 1005–1008.
SIGMOD-2013-LappasVGT #named #process: STEM: a spatio-temporal miner for bursty activity (TL, MRV, DG, VJT), pp. 1021–1024.
SIGMOD-2013-MiliarakiBGZ #scalability #sequence: Mind the gap: large-scale frequent sequence mining (IM, KB, RG, SZ), pp. 797–808.
SIGMOD-2013-MukherjiLBWRWR #interactive #named #parametricity: PARAS: interactive parameter space exploration for association rule mining (AM, XL, CRB, JW, EAR, MOW, CR), pp. 1017–1020.
SIGMOD-2013-OrdonezGGCBQ #algorithm #as a service #data mining #database #in the cloud #relational: Data mining algorithms as a service in the cloud exploiting relational database systems (CO, JGG, CGA, WC, VB, MSQ), pp. 1001–1004.
SIGMOD-2013-ZhuZQ #approach #graph #performance: A direct mining approach to efficient constrained graph pattern discovery (FZ, ZZ, QQ), pp. 821–832.
VLDB-2013-AmsterdamerGMS #named: CrowdMiner: Mining association rules from the crowd (YA, YG, TM, PS), pp. 1250–1253.
VLDB-2013-Bonomi #difference #privacy: Mining Frequent Patterns with Differential Privacy (LB), pp. 1422–1427.
VLDB-2013-LinMRRW #framework #named #online #parametricity: PARAS: A Parameter Space Framework for Online Association Mining (XL, AM, EAR, CR, MOW), pp. 193–204.
VLDB-2013-MousaviGZ #database #knowledge base #named: IBminer: A Text Mining Tool for Constructing and Populating InfoBox Databases and Knowledge Bases (HM, SG, CZ), pp. 1330–1333.
VLDB-2013-YangZHLRW #data type: Mining and Linking Patterns across Live Data Streams and Stream Archives (DY, KZ, MH, HL, EAR, MOW), pp. 1346–1349.
VLDB-2013-YuanMG #graph: Mining and Indexing Graphs for Supergraph Search (DY, PM, CLG), pp. 829–840.
ITiCSE-2013-MedinaPGR #data mining #education #learning #programming #using: Assistance in computer programming learning using educational data mining and learning analytics (CFM, JRPP, VMÁG, MdPPR), pp. 237–242.
ICSM-2013-LarssonH #debugging: Mining Telecom System Logs to Facilitate Debugging Tasks (AL, AHL), pp. 536–539.
ICSM-2013-MengMWB #repository: Mining Software Repositories for Accurate Authorship (XM, BPM, WRW, ARB), pp. 250–259.
ICSM-2013-QianPXJZ #logic #programming: Mining Logical Clones in Software: Revealing High-Level Business and Programming Rules (WQ, XP, ZX, SJ, WZ), pp. 40–49.
ICSM-2013-WangWYLLZ #categorisation #multi #repository: Mining Software Profile across Multiple Repositories for Hierarchical Categorization (TW, HW, GY, CXL, XL, PZ), pp. 240–249.
MSR-2013-AllamanisS13a #modelling #repository #source code #using: Mining source code repositories at massive scale using language modeling (MA, CAS), pp. 207–216.
MSR-2013-GhezziG: Replicating mining studies with SOFAS (GG, HCG), pp. 363–372.
MSR-2013-HemmatiNBKWHG #research: The MSR cookbook: mining a decade of research (HH, SN, OB, OK, WW, RH, MWG), pp. 343–352.
MSR-2013-HowardGPV #automation #semantics #word: Automatically mining software-based, semantically-similar words from comment-code mappings (MJH, SG, LLP, KVS), pp. 377–386.
MSR-2013-LamkanfiPD #dataset #debugging #eclipse #fault: The eclipse and mozilla defect tracking dataset: a genuine dataset for mining bug information (AL, JP, SD), pp. 203–206.
MSR-2013-WangDZCXZ #api #source code: Mining succinct and high-coverage API usage patterns from source code (JW, YD, HZ, KC, TX, DZ), pp. 319–328.
PASTE-2013-Lu #automation: Automatically mining program build information via signature matching (CDL), pp. 25–32.
SCAM-2013-SokolAG #named #repository #research: MetricMiner: Supporting researchers in mining software repositories (FZS, MFA, MAG), pp. 142–146.
WCRE-2013-HoraADV: Mining system specific rules from change patterns (AH, NA, SD, MTV), pp. 331–340.
WCRE-2013-JaafarGHK #anti #dependence: Mining the relationship between anti-patterns dependencies and fault-proneness (FJ, YGG, SH, FK), pp. 351–360.
WCRE-2013-NayrollesMV #detection #execution: Improving SOA antipatterns detection in Service Based Systems by mining execution traces (MN, NM, PV), pp. 321–330.
CIG-2013-ChoK #comparison #data mining: Comparison of human and AI bots in StarCraft with replay data mining (HCC, KJK), pp. 1–2.
CHI-2013-KumarSTLAKT #design #named #web: Webzeitgeist: design mining the web (RK, AS, CT, ML, SA, SRK, JOT), pp. 3083–3092.
CSCW-2013-ChoiHHLS #communication #social #using: Mining social relationship types in an organization using communication patterns (JC, SH, JH, GL, JS), pp. 295–302.
CSCW-2013-MinWHZ #smarttech #social: Mining smartphone data to classify life-facets of social relationships (JKM, JW, JIH, JZ), pp. 285–294.
DUXU-WM-2013-LiuVMM #big data #design #experience #framework #interactive #platform #visualisation: Designing Discovery Experience for Big Data Interaction: A Case of Web-Based Knowledge Mining and Interactive Visualization Platform (QL, MV, KPCM, AFM), pp. 543–552.
HIMI-LCCB-2013-SatonakaS #visualisation: Sales Strategy Mining System with Visualization of Action History (HS, WS), pp. 588–597.
HIMI-LCCB-2013-TakahashiA #using: User Needs Search Using Text Mining (YT, YA), pp. 607–615.
HIMI-LCCB-2013-YuL #approach #feedback: Exploring User Feedback of a E-Learning System: A Text Mining Approach (WBY, RL), pp. 182–191.
OCSC-2013-Abascal-MenaLZ #analysis #behaviour #twitter: User Generated Content: An Analysis of User Behavior by Mining Political Tweets (RAM, ÉLO, JSZH), pp. 3–12.
ICEIS-J-2013-KalsingITN13a #incremental #legacy #modelling #process #using: Re-learning of Business Process Models from Legacy System Using Incremental Process Mining (ACK, CI, LHT, GSdN), pp. 314–330.
ICEIS-v1-2013-al-KetbiC #data mining #integration: Integration of Decision Support Systems and Data Mining for Improved Decision Making (OaK, MC), pp. 482–489.
ICEIS-v1-2013-SonodaM #statistics: Mining Japanese Collocation by Statistical Indicators (TS, TM), pp. 381–388.
ICEIS-v2-2013-KalsingITN #incremental #learning #legacy #modelling #process #using: Evolutionary Learning of Business Process Models from Legacy Systems using Incremental Process Mining (ACK, CI, LHT, GSdN), pp. 58–69.
CIKM-2013-BonomiX #algorithm #difference #privacy: A two-phase algorithm for mining sequential patterns with differential privacy (LB, LX), pp. 269–278.
CIKM-2013-BrossE #automation #overview #sentiment: Automatic construction of domain and aspect specific sentiment lexicons for customer review mining (JB, HE), pp. 1077–1086.
CIKM-2013-Giles #big data #data mining #information management: Scholarly big data: information extraction and data mining (CLG), pp. 1–2.
CIKM-2013-HanW #graph #scalability: Mining frequent neighborhood patterns in a large labeled graph (JH, JRW), pp. 259–268.
CIKM-2013-JabbourSS #satisfiability #sequence: Boolean satisfiability for sequence mining (SJ, LS, YS), pp. 649–658.
CIKM-2013-KimCHZRD #feedback #modelling #topic: Mining causal topics in text data: iterative topic modeling with time series feedback (HDK, MC, MH, CZ, TAR, DD), pp. 885–890.
CIKM-2013-LiaoPPL #behaviour #mobile #on the #predict #smarttech: On mining mobile apps usage behavior for predicting apps usage in smartphones (ZXL, YCP, WCP, PRL), pp. 609–618.
CIKM-2013-LiHZW #clustering: Mining entity attribute synonyms via compact clustering (YL, BJPH, CZ, KW), pp. 867–872.
CIKM-2013-LiuLAM #personalisation #recommendation: Personalized point-of-interest recommendation by mining users’ preference transition (XL, YL, KA, CM), pp. 733–738.
CIKM-2013-LiuTCALC: Mining diabetes complication and treatment patterns for clinical decision support (LL, JT, YC, AA, WkL, ANC), pp. 279–288.
CIKM-2013-QianSYZL #query: Dynamic query intent mining from a search log stream (YnQ, TS, JY, QZ, CL), pp. 1205–1208.
CIKM-2013-SubbianAS #analysis #social: Content-centric flow mining for influence analysis in social streams (KS, CCA, JS), pp. 841–846.
CIKM-2013-Zhang0D #corpus #query: Mining a search engine’s corpus without a query pool (MZ, NZ, GD), pp. 29–38.
ECIR-2013-GalitskyK #web: A Web Mining Tool for Assistance with Creative Writing (BG, SOK), pp. 828–831.
KDD-2013-AnchuriZBGS #approximate #graph: Approximate graph mining with label costs (PA, MJZ, OB, SG, MS), pp. 518–526.
KDD-2013-ChengXCACG #named #realtime #social #social media: JobMiner: a real-time system for mining job-related patterns from social media (YC, YX, ZC, AA, ANC, SG), pp. 1450–1453.
KDD-2013-DanilevskyWTNCDWH #named #semistructured data #topic: AMETHYST: a system for mining and exploring topical hierarchies of heterogeneous data (MD, CW, FT, SN, GC, ND, LW, JH), pp. 1458–1461.
KDD-2013-EmersonWN #data mining #profiling: A data mining driven risk profiling method for road asset management (DE, JW, RN), pp. 1267–1275.
KDD-2013-FriezeGT #algorithm #graph #modelling #scalability: Algorithmic techniques for modeling and mining large graphs (AMAzING) (AMF, AG, CET), p. 1523.
KDD-2013-KaramshukNSNM #named #online: Geo-spotting: mining online location-based services for optimal retail store placement (DK, AN, SS, VN, CM), pp. 793–801.
KDD-2013-KongCY #classification #correlation #multi #network: Multi-label classification by mining label and instance correlations from heterogeneous information networks (XK, BC, PSY), pp. 614–622.
KDD-2013-LiWHHRY #ambiguity: Mining evidences for named entity disambiguation (YL, CW, FH, JH, DR, XY), pp. 1070–1078.
KDD-2013-PapadimitriouE #mobile #overview: Mining data from mobile devices: a survey of smart sensing and analytics (SP, TER), p. 1524.
KDD-2013-RanuHS #network: Mining discriminative subgraphs from global-state networks (SR, MXH, AKS), pp. 509–517.
KDD-2013-RautiainenSHYK #concept #online: An online system with end-user services: mining novelty concepts from tv broadcast subtitles (MR, JS, AH, MY, VK), pp. 1486–1489.
KDD-2013-Schadt #personalisation: Mining the digital universe of data to develop personalized cancer therapies (EES), p. 1134.
KDD-2013-ShakarianRCK #community #composition #distance #network #social: Mining for geographically disperse communities in social networks by leveraging distance modularity (PS, PR, DC, CK), pp. 1402–1409.
KDD-2013-ShenY #difference #graph #privacy: Mining frequent graph patterns with differential privacy (ES, TY), pp. 545–553.
KDD-2013-TangYGHLP #cyber-physical: Mining lines in the sand: on trajectory discovery from untrustworthy data in cyber-physical system (LAT, XY, QG, JH, AL, TFLP), pp. 410–418.
KDD-2013-TaoLHZCDDDGJKKLLLLOSTWZZ #multi #named: EventCube: multi-dimensional search and mining of structured and text data (FT, KHL, JH, CZ, XC, MD, ND, BD, JG, HJ, RK, AK, QL, YL, CXL, JL, NCO, ANS, RT, CW, DZ, BZ), pp. 1494–1497.
KDD-2013-WangDDZNTH #framework #recursion #topic: A phrase mining framework for recursive construction of a topical hierarchy (CW, MD, ND, YZ, PN, TT, JH), pp. 437–445.
KDD-2013-WangDYWCSI #clustering #data mining #framework #identification #towards: Towards long-lead forecasting of extreme flood events: a data mining framework for precipitation cluster precursors identification (DW, WD, KY, XW, PC, DLS, SI), pp. 1285–1293.
KDD-2013-WangLSG #multi: Mining evolutionary multi-branch trees from text streams (XW, SL, YS, BG), pp. 722–730.
KDD-2013-WuLYT #sequence: Mining high utility episodes in complex event sequences (CWW, YFL, PSY, VST), pp. 536–544.
KDD-2013-ZengJZLLLSZLDLW #data mining #distributed #named #performance: FIU-Miner: a fast, integrated, and user-friendly system for data mining in distributed environment (CZ, YJ, LZ, JL, LL, HL, CS, WZ, TL, BD, ML, PW), pp. 1506–1509.
KDIR-KMIS-2013-GengUA #algorithm: Trajectory Pattern Mining in Practice — Algorithms for Mining Flock Patterns from Trajectories (XG, TU, HA), pp. 143–151.
KDIR-KMIS-2013-MeiselBI #query: Mining the Long Tail of Search Queries — Finding Profitable Patterns (MM, MB, AI), pp. 225–229.
KDIR-KMIS-2013-PereiraRT #data mining #source code #student: Extraction Student Dropout Patterns with Data Mining Techniques in Undergraduate Programs (RTP, ACR, JJT), pp. 136–142.
KDIR-KMIS-2013-PfeiferP #taxonomy: Mapping Text Mining Taxonomies (KP, EP), pp. 5–16.
KDIR-KMIS-2013-RauchS #case study #using: Using Domain Knowledge in Association Rules Mining — Case Study (JR, MS), pp. 104–111.
MLDM-2013-AllahSG #algorithm #array #dataset #performance #scalability: An Efficient and Scalable Algorithm for Mining Maximal — High Confidence Rules from Microarray Dataset (WZAA, YKES, FFMG), pp. 352–366.
MLDM-2013-DittakanCC #case study #comparative #image: Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland (KD, FC, RC), pp. 260–274.
MLDM-2013-GaoD #data mining #distributed #performance #using: Improving the Efficiency of Distributed Data Mining Using an Adjustment Work Flow (JG, JD), pp. 69–83.
MLDM-2013-LiM #community #network #topic: Mining Groups of Common Interest: Discovering Topical Communities with Network Flows (LL, NDM), pp. 405–420.
MLDM-2013-ValencioKMSM #3d #data mining #visualisation: 3D Geovisualisation Techniques Applied in Spatial Data Mining (CRV, TK, CAdM, RCGdS, JMM), pp. 57–68.
SEKE-2013-Al-MsiedeenSHUVS #concept analysis #object-oriented #semantics #source code #using: Mining Features from the Object-Oriented Source Code of a Collection of Software Variants Using Formal Concept Analysis and Latent Semantic Indexing (RAM, ADS, MH, CU, SV, HES), pp. 244–249.
SEKE-2013-DelfimG #coordination #multi #slicing #using: Multiple Coordinated Views to Support Aspect Mining Using Program Slicing (FMD, REG), pp. 531–536.
SEKE-2013-MaffortVBHAM #design pattern #using: Mining Architectural Patterns Using Association Rules (CAM, MTV, RdSB, AH, NA, JM), pp. 375–380.
SEKE-2013-MarcalGCJ #identification #repository #using: Mining Software Repository to Identify Crosscutting Concerns Using Combined Techniques (IM, REG, RCMC, COJ), pp. 338–343.
SEKE-2013-PytelBG #validation: Proposal and Validation of a Feasibility Model for Information Mining Projects (PP, PB, RGM), pp. 83–88.
SIGIR-2013-GuoJLYA #interactive #mobile #predict #web: Mining touch interaction data on mobile devices to predict web search result relevance (QG, HJ, DL, SY, EA), pp. 153–162.
SIGIR-2013-JiangN #topic #web: Mining web search topics with diverse spatiotemporal patterns (DJ, WN), pp. 881–884.
SIGIR-2013-SakaiDYLZKSI #summary #topic: Summary of the NTCIR-10 INTENT-2 task: subtopic mining and search result diversification (TS, ZD, TY, YL, MZ, MPK, RS, MI), pp. 761–764.
PLEASE-2013-HuangYKHU #analysis #domain-specific language #repository #towards: Domain analysis for mining software repositories: Towards feature-based DSL construction (CH, KY, YK, KH, NU), pp. 41–44.
SPLC-2013-FerrariSd #documentation #natural language: Mining commonalities and variabilities from natural language documents (AF, GOS, FD), pp. 116–120.
SAS-2013-PelegSYY #automaton #specification: Symbolic Automata for Static Specification Mining (HP, SS, EY, HY), pp. 63–83.
RE-2013-MasseyEAS #analysis #automation #documentation #policy #requirements: Automated text mining for requirements analysis of policy documents (AKM, JE, AIA, PPS), pp. 4–13.
ASE-2013-FahlandLM: Mining branching-time scenarios (DF, DL, SM), pp. 443–453.
ASE-2013-RegerBR #approach #parametricity #specification: A pattern-based approach to parametric specification mining (GR, HB, DER), pp. 658–663.
ASE-2013-WongYT #automation #generative #named: AutoComment: Mining question and answer sites for automatic comment generation (EW, JY, LT), pp. 562–567.
ESEC-FSE-2013-SchurRZ #behaviour #enterprise #modelling #web: Mining behavior models from enterprise web applications (MS, AR, AZ), pp. 422–432.
ESEC-FSE-2013-SunK #debugging: Mining succinct predicated bug signatures (CS, SCK), pp. 576–586.
ICSE-2013-BettenburgB #development: Deciphering the story of software development through frequent pattern mining (NB, AB), pp. 1197–1200.
ICSE-2013-SharTB #hybrid #injection #program analysis #sql #using: Mining SQL injection and cross site scripting vulnerabilities using hybrid program analysis (LKS, HBKT, LCB), pp. 642–651.
SAC-2013-AccorsiSM #on the #process #security: On the exploitation of process mining for security audits: the process discovery case (RA, TS, GM), pp. 1462–1468.
SAC-2013-CameronCL #memory management #set: Stream mining of frequent sets with limited memory (JJC, AC, CKSL), pp. 173–175.
SAC-2013-DurelliSADC #overview: A systematic review on mining techniques for crosscutting concerns (RSD, DSMS, NA, MED, VVdC), pp. 1080–1087.
SAC-2013-Fournier-VigerT #named: TNS: mining top-k non-redundant sequential rules (PFV, VST), pp. 164–166.
SAC-2013-LeoniA #process #using: Data-aware process mining: discovering decisions in processes using alignments (MdL, WMPvdA), pp. 1454–1461.
SAC-2013-LiZSL #approach #graph #named #novel: WAVE-CIA: a novel CIA approach based on call graph mining (BL, QZ, XS, HL), pp. 1000–1005.
SAC-2013-MaunzVH #graph: Out-of-bag discriminative graph mining (AM, DV, CH), pp. 109–114.
SAC-2013-ZhangHMZMM #data type: Mining frequent itemsets over tuple-evolving data streams (CZ, YH, MM, CZ, HM, FM), pp. 267–274.
GPCE-2013-0001RN #abstract syntax tree #declarative #fine-grained #source code: Declarative visitors to ease fine-grained source code mining with full history on billions of AST nodes (RD, HR, TNN), pp. 23–32.
DATE-2013-LagraaTP #concurrent #data access #data mining #identification #memory management #simulation: Data mining MPSoC simulation traces to identify concurrent memory access patterns (SL, AT, FP), pp. 755–760.
FASE-2013-SanthiarPK #api #testing: Discovering Math APIs by Mining Unit Tests (AS, OP, AK), pp. 327–342.
ICTSS-2013-ElyasovPH #algebra #specification: Guided Algebraic Specification Mining for Failure Simplification (AE, ISWBP, JH), pp. 223–238.
DocEng-2012-WidlocherM #corpus #framework #platform: The Glozz platform: a corpus annotation and mining tool (AW, YM), pp. 171–180.
SIGMOD-2012-AkogluCKKF #graph #named #scalability #visualisation: OPAvion: mining and visualization in large graphs (LA, DHC, UK, DK, CF), pp. 717–720.
SIGMOD-2012-FaloutsosK #algorithm #graph #scalability: Managing and mining large graphs: patterns and algorithms (CF, UK), pp. 585–588.
SIGMOD-2012-MongioviBRSPF #named #network: SigSpot: mining significant anomalous regions from time-evolving networks (MM, PB, RR, AKS, EEP, CF), p. 865.
SIGMOD-2012-ShaoWX #graph #implementation #scalability: Managing and mining large graphs: systems and implementations (BS, HW, YX), pp. 589–592.
VLDB-2012-LiQSC #difference #named #privacy: PrivBasis: Frequent Itemset Mining with Differential Privacy (NL, WHQ, DS, JC), pp. 1340–1351.
VLDB-2012-SachanB #statistics #string #using: Mining Statistically Significant Substrings using the Chi-Square Statistic (MS, AB), pp. 1052–1063.
VLDB-2012-SilvaMZ #correlation #graph #scalability: Mining Attribute-structure Correlated Patterns in Large Attributed Graphs (AS, WMJ, MJZ), pp. 466–477.
VLDB-2012-SunHYY #analysis #approach #network: Mining Knowledge from Interconnected Data: A Heterogeneous Information Network Analysis Approach (YS, JH, XY, PSY), pp. 2022–2023.
VLDB-2012-TongCCY #database #nondeterminism: Mining Frequent Itemsets over Uncertain Databases (YT, LC, YC, PSY), pp. 1650–1661.
VLDB-2013-ZengNC12 #on the: On differentially private frequent itemset mining (CZ, JFN, JYC), pp. 25–36.
WCRE-J-2009-LoRRV12 #algorithm #evaluation #quantifier: Mining quantified temporal rules: Formalism, algorithms, and evaluation (DL, GR, VPR, KV), pp. 743–759.
CSMR-2012-HashimotoM #analysis #fine-grained: Enhancing History-Based Concern Mining with Fine-Grained Change Analysis (MH, AM), pp. 75–84.
CSMR-2012-NadiH #detection #linux #variability: Mining Kbuild to Detect Variability Anomalies in Linux (SN, RCH), pp. 107–116.
CSMR-2012-PetersZ #repository #smell #using: Evaluating the Lifespan of Code Smells using Software Repository Mining (RP, AZ), pp. 411–416.
ICPC-2012-PanichellaAPMC #developer #source code: Mining source code descriptions from developer communications (SP, JA, MDP, AM, GC), pp. 63–72.
MSR-2012-BaysalHG #development: Mining usage data and development artifacts (OB, RH, MWG), pp. 98–107.
MSR-2012-Breckel #comparison #database #debugging #detection #fault #scalability: Error mining: Bug detection through comparison with large code databases (AB), pp. 175–178.
MSR-2012-HarmanJZ #analysis: App store mining and analysis: MSR for app stores (MH, YJ, YZ), pp. 108–111.
MSR-2012-Hindle #power management: Green mining: A methodology of relating software change to power consumption (AH), pp. 78–87.
MSR-2012-KeivanlooFHENPR #framework #linked data #open data #platform #repository: A Linked Data platform for mining software repositories (IK, CF, AH, ME, CN, GP, JR), pp. 32–35.
MSR-2012-ReinaR #android #locality: Mining for localization in Android (LAR, GR), pp. 136–139.
MSR-2012-ShihabKB #android #challenge #framework #platform: Mining challenge 2012: The Android platform (ES, YK, PB), pp. 112–115.
MSR-2012-SinhaMG #android #named: MINCE: Mining change history of Android project (VSS, SM, MG), pp. 132–135.
WCRE-2012-TeytonFB #graph #library #migration: Mining Library Migration Graphs (CT, JRF, XB), pp. 289–298.
WCRE-2012-ZiftciK #data mining #feature model #using: Feature Location Using Data Mining on Existing Test-Cases (CZ, IK), pp. 155–164.
IFL-2012-WuMBS #case study #experience #lazy evaluation: Pure and Lazy λ Mining — An Experience Report (NW, JPM, JB, WS), pp. 207–223.
AIIDE-2012-GowCCM #experience #process: Mining Rules from Player Experience and Activity Data (JG, SC, PAC, PM).
CAiSE-2012-EngelAZPW #case study #modelling #process: Mining Inter-organizational Business Process Models from EDI Messages: A Case Study from the Automotive Sector (RE, WMPvdA, MZ, CP, HW), pp. 222–237.
CAiSE-2012-LyIMR #data transformation #process #semantics: Data Transformation and Semantic Log Purging for Process Mining (LTL, CI, JM, SRM), pp. 238–253.
ICEIS-J-2012-AyresS12a #similarity: Exploring Similarity Relations According to Different Contexts in Mining Generalized Association Rules (RMJA, MTPS), pp. 137–152.
ICEIS-J-2012-FabbriHTBZS12a #using #visualisation: Using Information Visualization and Text Mining to Facilitate the Conduction of Systematic Literature Reviews (SF, EMH, ADT, AB, AZ, CS), pp. 243–256.
ICEIS-v1-2012-AyresS #fuzzy #ontology #similarity #using: Mining Generalized Association Rules using Fuzzy Ontologies with Context-based Similarity (RMJA, MTPS), pp. 74–83.
ICEIS-v1-2012-ZianiRO #approach #constraints #multi: A Constraint-based Mining Approach for Multi-attribute Index Selection (BZ, FR, YO), pp. 93–98.
ICEIS-v2-2012-LukaszewskiJL #data mining #ontology #semantics #using: Attribute Value Ontology — Using Semantics in Data Mining (TL, JJ, AL), pp. 329–334.
CIKM-2012-AmiriC #sentiment: Mining sentiment terminology through time (HA, TSC), pp. 2060–2064.
CIKM-2012-BhuiyanMH #interactive: Interactive pattern mining on hidden data: a sampling-based solution (MB, SM, MAH), pp. 95–104.
CIKM-2012-DaiZLP #web: Mining coherent anomaly collections on web data (HD, FZ, EPL, HP), pp. 1557–1561.
CIKM-2012-DongFSZY #framework: A general framework to encode heterogeneous information sources for contextual pattern mining (WD, WF, LS, CZ, XY), pp. 65–74.
CIKM-2012-HaiCC: One seed to find them all: mining opinion features via association (ZH, KC, GC), pp. 255–264.
CIKM-2012-HuHXLUZ #analysis: Finding nuggets in IP portfolios: core patent mining through textual temporal analysis (PH, MH, PX, WL, AKU, XZ), pp. 1819–1823.
CIKM-2012-IntagornL #approach #probability #social: A probabilistic approach to mining geospatial knowledge from social annotations (SI, KL), pp. 1717–1721.
CIKM-2012-KacimiG #named: MOUNA: mining opinions to unveil neglected arguments (MK, JG), pp. 2722–2724.
CIKM-2012-KimZRDHCL #named #topic: InCaToMi: integrative causal topic miner between textual and non-textual time series data (HDK, CZ, TAR, DD, MH, MC, CCL), pp. 2689–2691.
CIKM-2012-KozawaAK #database #gpu #nondeterminism #probability: GPU acceleration of probabilistic frequent itemset mining from uncertain databases (YK, TA, HK), pp. 892–901.
CIKM-2012-LiSSTDL #microblog #topic: Mining topic-level opinion influence in microblog (DL, XS, GS, JT, YD, ZL), pp. 1562–1566.
CIKM-2012-LiuCBLR #graph: Utilizing common substructures to speedup tensor factorization for mining dynamic graphs (WL, JC, JB, CL, KR), pp. 435–444.
CIKM-2012-LiuQ #generative: Mining high utility itemsets without candidate generation (ML, JFQ), pp. 55–64.
CIKM-2012-MoghaddamE #design #modelling #on the: On the design of LDA models for aspect-based opinion mining (SM, ME), pp. 803–812.
CIKM-2012-NiuRWY #effectiveness #web: An effective rule miner for instance matching in a web of data (XN, SR, HW, YY), pp. 1085–1094.
CIKM-2012-QiYZZ #multi: Mining noisy tagging from multi-label space (ZQ, MY, Z(Z, ZZ), pp. 1925–1929.
CIKM-2012-RiondatoDFU #algorithm #approximate #named #parallel #pipes and filters #random: PARMA: a parallel randomized algorithm for approximate association rules mining in MapReduce (MR, JAD, RF, EU), pp. 85–94.
CIKM-2012-TangZLW #quality #recommendation: Incorporating occupancy into frequent pattern mining for high quality pattern recommendation (LT, LZ, PL, MW), pp. 75–84.
CIKM-2012-TanLZ: Mining long-lasting exploratory user interests from search history (BT, YL, CZ), pp. 1477–1481.
CIKM-2012-WangH0 #framework #image #learning #web: A unified learning framework for auto face annotation by mining web facial images (DW, SCHH, YH), pp. 1392–1401.
CIKM-2012-WicaksonoM: Mining advices from weblogs (AFW, SHM), pp. 2347–2350.
CIKM-2012-YamamotoSIYWT #clustering #query: The wisdom of advertisers: mining subgoals via query clustering (TY, TS, MI, CY, JRW, KT), pp. 505–514.
CIKM-2012-YangTKZLDLW #learning #network: Mining competitive relationships by learning across heterogeneous networks (YY, JT, JK, YZ, JL, YD, TL, LW), pp. 1432–1441.
CIKM-2012-ZhuGCL #behaviour #query #recommendation: More than relevance: high utility query recommendation by mining users’ search behaviors (XZ, JG, XC, YL), pp. 1814–1818.
ICPR-2012-DaiFZ #detection: Mining sub-categories for object detection (JD, JF, JZ), pp. 3260–3263.
ICPR-2012-FuscoWY: Mining residential household information from low-resolution smart meter data (FF, MW, JWY), pp. 3545–3548.
ICPR-2012-ZhangZHHT #detection #semantics: Semantic windows mining in sliding window based object detection (JZ, XZ, YH, KH, TT), pp. 3264–3267.
KDD-2012-BatalFHMH #detection #multi: Mining recent temporal patterns for event detection in multivariate time series data (IB, DF, JH, FM, MH), pp. 280–288.
KDD-2012-BodenGHS #graph #multi: Mining coherent subgraphs in multi-layer graphs with edge labels (BB, SG, HH, TS), pp. 1258–1266.
KDD-2012-ChanLLBR #graph #multi #named: SeqiBloc: mining multi-time spanning blockmodels in dynamic graphs (JC, WL, CL, JB, KR), pp. 651–659.
KDD-2012-DuivesteijnFK #distance #modelling: Different slopes for different folks: mining for exceptional regression models with cook’s distance (WD, AF, AJK), pp. 868–876.
KDD-2012-FengHKBP #graph: Summarization-based mining bipartite graphs (JF, XH, BK, CB, CP), pp. 1249–1257.
KDD-2012-GalbrunM #interactive #named #visualisation: Siren: an interactive tool for mining and visualizing geospatial redescriptions (EG, PM), pp. 1544–1547.
KDD-2012-GuptaGSH #community #detection: Integrating community matching and outlier detection for mining evolutionary community outliers (MG, JG, YS, JH), pp. 859–867.
KDD-2012-Han #network: Mining heterogeneous information networks: the next frontier (JH), pp. 2–3.
KDD-2012-HendersonGETBAKFL #graph #named #scalability: RolX: structural role extraction & mining in large graphs (KH, BG, TER, HT, SB, LA, DK, CF, LL), pp. 1231–1239.
KDD-2012-Holmes #data mining: Developing data mining applications (GH), p. 225.
KDD-2012-LappasVG #invariant #performance: Efficient and domain-invariant competitor mining (TL, GV, DG), pp. 408–416.
KDD-2012-Li12b #algorithm #graph #nondeterminism: Algorithms for mining uncertain graph data (JL), p. 813.
KDD-2012-Lin #case study #data mining #experience #machine learning: Experiences and lessons in developing industry-strength machine learning and data mining software (CJL), p. 1176.
KDD-2012-LiuBEWFZ #comparison #scalability: Mining large-scale, sparse GPS traces for map inference: comparison of approaches (XL, JB, JE, YW, GF, YZ), pp. 669–677.
KDD-2012-LiWH: Mining event periodicity from incomplete observations (ZL, JW, JH), pp. 444–452.
KDD-2012-MaoCCLKB #approach #data mining #monitoring #realtime: An integrated data mining approach to real-time clinical monitoring and deterioration warning (YM, WC, YC, CL, MK, TCB), pp. 1140–1148.
KDD-2012-MatsubaraSFIY #performance: Fast mining and forecasting of complex time-stamped events (YM, YS, CF, TI, MY), pp. 271–279.
KDD-2012-MukherjeeL: Mining contentions from discussions and debates (AM, BL), pp. 841–849.
KDD-2012-RakthanmanonCMBWZZK #sequence: Searching and mining trillions of time series subsequences under dynamic time warping (TR, BJLC, AM, GEAPAB, MBW, QZ, JZ, EJK), pp. 262–270.
KDD-2012-ShaferRBAGF #approach #monitoring #named: RainMon: an integrated approach to mining bursty timeseries monitoring data (IS, KR, VNB, YA, GRG, CF), pp. 1158–1166.
KDD-2012-SondhiSTZ #framework #graph #named: SympGraph: a framework for mining clinical notes through symptom relation graphs (PS, JS, HT, CZ), pp. 1167–1175.
KDD-2012-TangWYHZYGHXLU #analysis #named #topic: PatentMiner: topic-driven patent analysis and mining (JT, BW, YY, PH, YZ, XY, BG, MH, PX, WL, AKU), pp. 1366–1374.
KDD-2012-TongCY #named #nondeterminism: UFIMT: an uncertain frequent itemset mining toolbox (YT, LC, PSY), pp. 1508–1511.
KDD-2012-WoznicaNK #feature model #robust: Model mining for robust feature selection (AW, PN, AK), pp. 913–921.
KDD-2012-WuSTY: Mining top-K high utility itemsets (CWW, BES, VST, PSY), pp. 78–86.
KDD-2012-YinZC #algorithm #named #performance: USpan: an efficient algorithm for mining high utility sequential patterns (JY, ZZ, LC), pp. 660–668.
KDD-2012-YuDSW #feature model #streaming: Mining emerging patterns by streaming feature selection (KY, WD, DAS, XW), pp. 60–68.
KDD-2012-YuZSWWQZ #analysis #data mining #in the cloud #named #network #social: BC-PDM: data mining, social network analysis and text mining system based on cloud computing (LY, JZ, WCS, BW, BW, LQ, BRZ), pp. 1496–1499.
KDD-2012-ZhangL #component #constraints #rank #recognition: Mining discriminative components with low-rank and sparsity constraints for face recognition (QZ, BL), pp. 1469–1477.
KDIR-2012-ArbelaitzGLMPP #adaptation #clustering #navigation #profiling #using: Adaptation of the User Navigation Scheme using Clustering and Frequent Pattern Mining Techiques for Profiling (OA, IG, AL, JM, JMP, IP), pp. 187–192.
KDIR-2012-ArbelaitzGLMPP12a #adaptation #web: Enhancing a Web Usage Mining based Tourism Website Adaptation with Content Information (OA, IG, AL, JM, JMP, IP), pp. 287–292.
KDIR-2012-BhattacharjeeBG #data mining #network #optimisation #using: Product Assortment Decisions for a Network of Retail Stores using Data Mining with Optimization (SB, FB, RDG), pp. 319–323.
KDIR-2012-GayLM #approach #constraints #multi #sequence: Constraint-programming Approach for Multiset and Sequence Mining (PG, BL, JM), pp. 212–220.
KEOD-2012-KhairMZ #data mining #education #roadmap #student #using: Creating an Educational Roadmap for Engineering Students via an Optimal and Iterative Yearly Regression Tree using Data Mining (MK, CEM, WZ), pp. 43–52.
KMIS-2012-PortelaPS #data mining #modelling #pervasive #predict: Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine (FP, FP, MFS), pp. 81–88.
MLDM-2012-LiHO #approach #correlation: Top-N Minimization Approach for Indicative Correlation Change Mining (AL, MH, YO), pp. 102–116.
MLDM-2012-MacchiaCM #modelling #network #ranking: Mining Ranking Models from Dynamic Network Data (LM, MC, DM), pp. 566–577.
MLDM-2012-MondalPMMB #approach #clustering #concept analysis #using: A New Approach for Association Rule Mining and Bi-clustering Using Formal Concept Analysis (KCM, NP, AM, UM, SB), pp. 86–101.
MLDM-2012-PipanmaekapornL #effectiveness: A Pattern Discovery Model for Effective Text Mining (LP, YL), pp. 540–554.
RecSys-2012-YangCZLY #feedback #music #recommendation: Local implicit feedback mining for music recommendation (DY, TC, WZ, QL, YY), pp. 91–98.
SEKE-2012-WangXC #linear #network #social: Sparse Linear Influence Model for Hot User Selection on Mining a Social Network (YW, GX, SKC), pp. 1–6.
SEKE-2012-ZhangLS #graph #impact analysis: Mining Call Graph for Change Impact Analysis (QZ, BL, XS), pp. 7–12.
SIGIR-2012-CareniniM: Methods for mining and summarizing text conversations (GC, GM), pp. 1178–1179.
SIGIR-2012-GaoWL #graph #information retrieval #learning #scalability: Large-scale graph mining and learning for information retrieval (BG, TW, TYL), pp. 1194–1195.
SIGIR-2012-HuQLJPZ #query #topic: Mining query subtopics from search log data (YH, YnQ, HL, DJ, JP, QZ), pp. 305–314.
SIGIR-2012-Khatiban #trust #using: Building reputation and trust using federated search and opinion mining (SK), p. 994.
SIGIR-2012-MoghaddamE: Aspect-based opinion mining from product reviews (SM, ME), p. 1184.
SIGIR-2012-RaeMPB #web: Mining the web for points of interest (AR, VM, AP, HB), pp. 711–720.
SIGIR-2012-RaveendranC #lightweight #summary: Lightweight contrastive summarization for news comment mining (GR, CLAC), pp. 1103–1104.
SIGIR-2012-YangCZY #collaboration: Collaborative filtering with short term preferences mining (DY, TC, WZ, YY), pp. 1043–1044.
RE-2012-Yi0ZJM #constraints #feature model #modelling: Mining binary constraints in the construction of feature models (LY, WZ, HZ, ZJ, HM), pp. 141–150.
ASE-2012-DingFLLZSX #online #repository: Healing online service systems via mining historical issue repositories (RD, QF, JGL, QL, DZ, JS, TX), pp. 318–321.
FSE-2012-CanaveraEM #adaptation #execution: Mining the execution history of a software system to infer the best time for its adaptation (KRC, NE, SM), p. 18.
ICSE-2012-Butler #identifier #java: Mining Java class identifier naming conventions (SB), pp. 1641–1643.
ICSE-2012-HanDGZX #debugging #in the large #performance #stack: Performance debugging in the large via mining millions of stack traces (SH, YD, SG, DZ, TX), pp. 145–155.
ICSE-2012-Hindle #power management: Green mining: Investigating power consumption across versions (AH), pp. 1301–1304.
ICSE-2012-HuangLXW #recommendation #repository #xml: Mining application repository to recommend XML configuration snippets (SH, YL, YX, WW), pp. 1451–1452.
ICSE-2012-Keivanloo #integration #online #repository: Online sharing and integration of results from mining software repositories (IK), pp. 1644–1646.
ICSE-2012-NaganoNKAHUF #repository #scalability #using: Using the GPGPU for scaling up Mining Software Repositories (RN, HN, YK, BA, KH, NU, AF), pp. 1435–1436.
ICSE-2012-PradelG #automation #debugging #detection #generative #specification #testing: Leveraging test generation and specification mining for automated bug detection without false positives (MP, TRG), pp. 288–298.
ICSE-2012-SharT #injection #predict #sql: Mining input sanitization patterns for predicting SQL injection and cross site scripting vulnerabilities (LKS, HBKT), pp. 1293–1296.
ICSE-2012-SunSPR #static analysis: Extending static analysis by mining project-specific rules (BS, GS, AP, BR), pp. 1054–1063.
SAC-2012-AccorsiS #consistency #on the #process #security: On the exploitation of process mining for security audits: the conformance checking case (RA, TS), pp. 1709–1716.
SAC-2012-DiamantiniPS #repository #workflow: Mining usage patterns from a repository of scientific workflows (CD, DP, ES), pp. 152–157.
SAC-2012-LangohrT: A model for mining relevant and non-redundant information (LL, HT), pp. 132–137.
SAC-2012-LeungS #constraints: A new class of constraints for constrained frequent pattern mining (CKSL, LS), pp. 199–204.
SAC-2012-WangTWWG #algorithm #behaviour #empirical #evaluation #process: An empirical evaluation of process mining algorithms based on structural and behavioral similarities (JW, ST, LW, RKW, QG), pp. 211–213.
SAC-2012-WangZHHZWT #mobile #recommendation: Context-aware role mining for mobile service recommendation (JW, CZ, CH, LH, LZ, RKW, JT), pp. 173–178.
CASE-2012-DunnTRR #navigation: High accuracy inertial navigation for underground mining machinery (MTD, JPT, PBR, DCR), pp. 1179–1183.
CASE-2012-HoSY #data mining #modelling: Data Mining of Life Log for Developing a User model-based Service Application (YH, ESS, TY), pp. 757–760.
DATE-2012-MitraBD #formal method #ranking: Formal methods for ranking counterexamples through assumption mining (SM, AB, PD), pp. 911–916.
PDP-2012-SaenkoK #algorithm #design #evaluation #performance #problem #search-based: Design and Performance Evaluation of Improved Genetic Algorithm for Role Mining Problem (IS, IVK), pp. 269–274.
PDP-2012-SilvestriO #named: gpuDCI: Exploiting GPUs in Frequent Itemset Mining (CS, SO), pp. 416–425.
ICLP-2012-BlockeelBBCP #data mining #machine learning #modelling #problem: Modeling Machine Learning and Data Mining Problems with FO(·) (HB, BB, MB, BdC, SDP, MD, AL, JR, SV), pp. 14–25.
HT-2011-SahW #automation #fuzzy #metadata #using: Automatic mining of cognitive metadata using fuzzy inference (MS, VW), pp. 37–46.
SIGMOD-2011-OrdonezP #algorithm #data mining: One-pass data mining algorithms in a DBMS with UDFs (CO, SKP), pp. 1217–1220.
SIGMOD-2011-PoundPT #approach #web: Facet discovery for structured web search: a query-log mining approach (JP, SP, PT), pp. 169–180.
SIGMOD-2011-ZhangZD #corpus #estimation #performance: Mining a search engine’s corpus: efficient yet unbiased sampling and aggregate estimation (MZ, NZ, GD), pp. 793–804.
TPDL-2011-KnothRZ #repository #semantics #using: Connecting Repositories in the Open Access Domain Using Text Mining and Semantic Data (PK, VR, ZZ), pp. 483–487.
TPDL-2011-TsatsaronisVTRNSZ #graph #how #modelling: How to Become a Group Leader? or Modeling Author Types Based on Graph Mining (GT, IV, ST, MR, KN, MS, MZ), pp. 15–26.
VLDB-2011-YangPS #graph #multi #performance: Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining (XY, SP, PS), pp. 231–242.
VLDB-2011-ZhuQLYHY #network #scalability: Mining Top-K Large Structural Patterns in a Massive Network (FZ, QQ, DL, XY, JH, PSY), pp. 807–818.
VLDB-2012-BarskyKWH11 #correlation #dataset #scalability #taxonomy: Mining Flipping Correlations from Large Datasets with Taxonomies (MB, SK, TW, JH), pp. 370–381.
VLDB-2012-LiuZW11: Controlling False Positives in Association Rule Mining (GL, HZ, LW), pp. 145–156.
CSMR-2011-BelderrarKGAG #architecture #evolution #identification #object-oriented: Sub-graph Mining: Identifying Micro-architectures in Evolving Object-Oriented Software (AB, SK, YGG, GA, PG), pp. 171–180.
CSMR-2011-LamkanfiDSV #algorithm #debugging #predict: Comparing Mining Algorithms for Predicting the Severity of a Reported Bug (AL, SD, QDS, TV), pp. 249–258.
CSMR-2011-PoncinSB #process #repository: Process Mining Software Repositories (WP, AS, MvdB), pp. 5–14.
ICPC-2011-Medini #automation #concept #execution #scalability: Scalable Automatic Concept Mining from Execution Traces (SM), pp. 238–241.
ICSM-2011-ButlerWYS #java: Mining java class naming conventions (SB, MW, YY, HS), pp. 93–102.
ICSM-2011-DAmbrosR #effectiveness #repository: Effective mining of software repositories (MD, RR), p. 598.
ICSM-2011-PirzadehHS #analysis #execution: Exploiting text mining techniques in the analysis of execution traces (HP, AHL, MS), pp. 223–232.
ICSM-2011-TarvoZC #algorithm #branch #integration #multi #version control: An integration resolution algorithm for mining multiple branches in version control systems (AT, TZ, JC), pp. 402–411.
ICSM-2011-YousefiS #distributed #identification: Identifying distributed features in SOA by mining dynamic call trees (AY, KS), pp. 73–82.
MSR-2011-Whitehead #data mining #game studies #what: Fantasy, farms, and freemium: what game data mining teaches us about retention, conversion, and virality (JW), p. 1.
WCRE-2011-NadiH #linux: Make it or Break it: Mining Anomalies from Linux Kbuild (SN, RCH), pp. 315–324.
CIG-2011-AsheSK #data mining #machine learning #named: Keynotes: Data mining and machine learning applications in MMOs (GA, NRS, JHK).
CHI-2011-LeeKF #behaviour #design #persuasion: Mining behavioral economics to design persuasive technology for healthy choices (MKL, SBK, JF), pp. 325–334.
HCI-UA-2011-LinHLYH #using: Using Grounded Theory and Text Mining to Find Interesting Reading Materials for Slow EFL Learners (YCL, ClH, MHL, HFY, CFH), pp. 77–85.
HIMI-v2-2011-MozaffariM #classification #visual notation: A Classification Scheme for Characterizing Visual Mining (EM, SPM), pp. 46–54.
OCSC-2011-GaoQZ #social: Mining Social Relationships in Micro-blogging Systems (QG, QQ, XZ), pp. 110–119.
CAiSE-2011-BoseAZP #concept #process: Handling Concept Drift in Process Mining (RPJCB, WMPvdA, IZ, MP), pp. 391–405.
ICEIS-J-2011-WangN11a #named #nondeterminism: UF-Evolve: Uncertain Frequent Pattern Mining (SW, VTYN), pp. 98–116.
ICEIS-v1-2011-Cuzzocrea #approach #information management: A UML-extended Approach for Mining OLAP Data Cubes in Complex Knowledge Discovery Environments (AC), pp. 281–289.
ICEIS-v1-2011-SantosP #data mining #preprocessor #ubiquitous: Enabling Ubiquitous Data Mining in Intensive Care — Features Selection and Data Pre-processing (MS, FP), pp. 261–266.
ICEIS-v1-2011-ThitiprayoonwongseSS #data mining: Data Mining on Dengue Virus Disease (DT, PS, NS), pp. 32–41.
ICEIS-v1-2011-WangN #named #nondeterminism: UF-Evolve — Uncertain Frequent Pattern Mining (SW, VTYN), pp. 74–84.
ICEIS-v4-2011-Naderipour #ad hoc #industrial #process #using: Mining of Ad-hoc Business Processes using Microsoft Sharepoint, Nitro & Prom 6.0 — An Industrial Practice (FN), pp. 413–418.
CIKM-2011-DongZCZZLWO #database #named #performance: e-NSP: efficient negative sequential pattern mining based on identified positive patterns without database rescanning (XD, ZZ, LC, YZ, CZ, JL, WW, YO), pp. 825–830.
CIKM-2011-GuoZTG #data type #multi: Mining frequent patterns across multiple data streams (JG, PZ, JT, LG), pp. 2325–2328.
CIKM-2011-KimJHSZ #approach #corpus #graph: Mining entity translations from comparable corpora: a holistic graph mapping approach (JK, LJ, SwH, YIS, MZ), pp. 1295–1304.
CIKM-2011-KiselevaAB #case study #query: Mining query structure from click data: a case study of product queries (JK, EA, DB), pp. 2217–2220.
CIKM-2011-KrishnaswamyGG #data type #mobile #roadmap #ubiquitous: Advances in data stream mining for mobile and ubiquitous environments (SK, JG, MMG), pp. 2607–2608.
CIKM-2011-LoSZL #community #network #trust: Mining direct antagonistic communities in explicit trust networks (DL, DS, KZ, EPL), pp. 1013–1018.
CIKM-2011-OrdonezG #data mining #database #query #relational #sql: A data mining system based on SQL queries and UDFs for relational databases (CO, CGA), pp. 2521–2524.
CIKM-2011-XuJL #image #online #ranking: Retrieving and ranking unannotated images through collaboratively mining online search results (SX, HJ, FCML), pp. 485–494.
CIKM-2011-YeungJ #how #scalability #towards: Studying how the past is remembered: towards computational history through large scale text mining (CmAY, AJ), pp. 1231–1240.
CIKM-2011-ZhangJJ #framework: Promotional subspace mining with EProbe framework (YZ, YJ, WJ), pp. 2185–2188.
ECIR-2011-Carrillo-de-AlbornozPGD #analysis #overview #rating #sentiment: A Joint Model of Feature Mining and Sentiment Analysis for Product Review Rating (JCdA, LP, PG, AD), pp. 55–66.
KDD-2011-BatistaKMR #data mining: SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining (GEAPAB, EJK, AMN, ER), pp. 761–764.
KDD-2011-Bie #data mining #framework: An information theoretic framework for data mining (TDB), pp. 564–572.
KDD-2011-BifetHPG #data type #evolution #graph: Mining frequent closed graphs on evolving data streams (AB, GH, BP, RG), pp. 591–599.
KDD-2011-Boire #case study #data mining #lessons learnt: The practitioner’s viewpoint to data mining: key lessons learned in the trenches and case studies (RB), p. 785.
KDD-2011-Elder: Thriving as a data miner in the real world (JFEI), p. 786.
KDD-2011-GhotingKPK #algorithm #data mining #implementation #machine learning #named #parallel #pipes and filters #tool support: NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce (AG, PK, EPDP, RK), pp. 334–342.
KDD-2011-GoethalsMV #framework #interactive #named #visual notation: MIME: a framework for interactive visual pattern mining (BG, SM, JV), pp. 757–760.
KDD-2011-HendersonGLAETF #graph #recursion #using: It’s who you know: graph mining using recursive structural features (KH, BG, LL, LA, TER, HT, CF), pp. 663–671.
KDD-2011-Inchiosa #data mining #scalability #using: Accelerating large-scale data mining using in-database analytics (MEI), p. 778.
KDD-2011-JinWLYH #named #network #power of #social #social media: LikeMiner: a system for mining the power of “like” in social media networks (XJ, CW, JL, XY, JH), pp. 753–756.
KDD-2011-KaufmanRP #data mining #detection: Leakage in data mining: formulation, detection, and avoidance (SK, SR, CP), pp. 556–563.
KDD-2011-LathiaC: Mining mobility data to minimise travellers’ spending on public transport (NL, LC), pp. 1181–1189.
KDD-2011-McCloskeyKIKB #behaviour #data mining #using: From market baskets to mole rats: using data mining techniques to analyze RFID data describing laboratory animal behavior (DPM, MEK, SPI, IK, SBM), pp. 301–306.
KDD-2011-MohammedCFY #data mining: Differentially private data release for data mining (NM, RC, BCMF, PSY), pp. 493–501.
KDD-2011-MukerjeePG #algorithm #framework #linear #platform #semantics #sql: Linear scale semantic mining algorithms in microsoft SQL server’s semantic platform (KM, TP, SG), pp. 213–221.
KDD-2011-PatnaikBRPKH #case study #challenge #experience #sequence: Experiences with mining temporal event sequences from electronic medical records: initial successes and some challenges (DP, PB, NR, LP, BJK, DAH), pp. 360–368.
KDD-2011-QiYZZ #image: Mining partially annotated images (ZQ, MY, Z(Z, ZZ), pp. 1199–1207.
KDD-2011-RamageMD #modelling #topic: Partially labeled topic models for interpretable text mining (DR, CDM, STD), pp. 457–465.
KDD-2011-Rejto #data mining #information management #research: Knowledge discovery and data mining in pharmaceutical cancer research (PAR), p. 781.
KDD-2011-TattiC: Mining closed episodes with simultaneous events (NT, BC), pp. 1172–1180.
KDD-2011-TrasartiPNG: Mining mobility user profiles for car pooling (RT, FP, MN, FG), pp. 1190–1198.
KDD-2011-VijayaraghavanK #data mining #machine learning #online: Applications of data mining and machine learning in online customer care (RV, PVK), p. 779.
KDD-2011-ZhengSTLLC #challenge #data mining #information management #mobile: Applying data mining techniques to address disaster information management challenges on mobile devices (LZ, CS, LT, TL, SL, SCC), pp. 283–291.
KDIR-2011-AlouaouiTF #query: Querying and Mining Spatiotemporal Association Rules (HA, SYT, SF), pp. 402–405.
KDIR-2011-BonninBB #predict #web: Handling Tabbing and Backward References for Predictive Web Usage Mining (GB, AB, AB), pp. 503–509.
KDIR-2011-BressoBSMKSND #reduction #using: Use of Domain Knowledge for Dimension Reduction — Application to Mining of Drug Side Effects (EB, SB, MST, GM, ASK, MS, AN, MDD), pp. 271–276.
KDIR-2011-DAcuntoBDLPPS #3d #re-engineering: Inferential Mining for Reconstruction of 3D Cell Structures in Atomic Force Microscopy Imaging (MD, SB, SD, ML, MP, AP, OS), pp. 348–353.
KDIR-2011-HsiehY #case study: A Study of Profit Mining (YLH, DLY), pp. 510–514.
KDIR-2011-MukerjeePG #database #documentation #relational #semantics: Semantic Mining of Documents in a Relational Database (KM, TP, SG), pp. 146–158.
KDIR-2011-OmerBG #algorithm #motivation #using: A New Frequent Similar Tree Algorithm Motivated by Dom Mining — Using RTDM and its New Variant — SiSTeR (OB, RB, SG), pp. 238–243.
KDIR-2011-Vanetik #algorithm #graph #performance: A Fast Algorithm for Mining Graphs of Prescribed Connectivity (NV), pp. 5–13.
KDIR-2011-VanetikG #named: HashMax: A New Method for Mining Maximal Frequent Itemsets (NV, EG), pp. 140–145.
MLDM-2011-ChenER #parametricity #using: Mining Spatial Trajectories Using Non-parametric Density Functions (CSC, CFE, NJR), pp. 496–510.
MLDM-2011-Kessl #parallel #using: Static Load Balancing of Parallel Mining of Frequent Itemsets Using Reservoir Sampling (RK), pp. 553–567.
MLDM-2011-SimeonH #approach #correlation #difference #named #set: GENCCS: A Correlated Group Difference Approach to Contrast Set Mining (MS, RJH), pp. 140–154.
MLDM-2011-TalbertHT #data mining #framework #machine learning: A Machine Learning and Data Mining Framework to Enable Evolutionary Improvement in Trauma Triage (DAT, MH, ST), pp. 348–361.
SEKE-2011-CellierDFR #data mining #fault #locality #multi: Multiple Fault Localization with Data Mining (PC, MD, SF, OR), pp. 238–243.
SEKE-2011-LemosSLO #consistency #development #process: Conformance Checking of Software Development Processes Through Process Mining (AML, CCS, RMFL, CALO), pp. 654–659.
SEKE-2011-WuXKP #analysis #data mining #debugging #named #reliability: BUGMINER: Software Reliability Analysis Via Data Mining of Bug Reports (LW, BX, GEK, RJP), pp. 95–100.
SIGIR-2011-JiangPL #web: Enhancing web search by mining search and browse logs (DJ, JP, HL), pp. 1295–1296.
SIGIR-2011-KimKWHK #approach #classification: Authorship classification: a discriminative syntactic tree mining approach (SK, HK, TW, JH, HDK), pp. 455–464.
SIGIR-2011-LappasPS #network #social #using: Mining tags using social endorsement networks (TL, KP, TS), pp. 195–204.
SIGIR-2011-WangHH #image #search-based #web: Mining weakly labeled web facial images for search-based face annotation (DW, SCHH, YH), pp. 535–544.
SIGIR-2011-ZhengGYXBSHY #community #topic: Mining topics on participations for community discovery (GZ, JG, LY, SX, SB, ZS, DH, YY), pp. 445–454.
ECOOP-2011-MilevaWZ #evolution: Mining Evolution of Object Usage (YMM, AW, AZ), pp. 105–129.
PLDI-2011-DEliaDF: Mining hot calling contexts in small space (DCD, CD, IF), pp. 516–527.
REFSQ-2011-GervasiZ #requirements: Mining Requirements Links (VG, DZ), pp. 196–201.
ASE-2011-WuLWXM #specification: Iterative mining of resource-releasing specifications (QW, GL, QW, TX, HM), pp. 233–242.
ASE-2011-ZhengMLXK #testing #web: Mining test oracles of web search engines (WZ, HM, MRL, TX, IK), pp. 408–411.
ESEC-FSE-2011-Bettenburg #collaboration #development #repository: Mining development repositories to study the impact of collaboration on software systems (NB), pp. 376–379.
ESEC-FSE-2011-Schur #enterprise #specification: Experimental specification mining for enterprise applications (MS), pp. 388–391.
ICSE-2011-AthanasopoulosZVI #abstraction: Mining service abstractions (DA, AZ, PV, VI), pp. 944–947.
ICSE-2011-DumitruGHCMCM #on-demand #recommendation: On-demand feature recommendations derived from mining public product descriptions (HD, MG, NH, JCH, BM, CCH, MM), pp. 181–190.
ICSE-2011-Kumar #concurrent #distributed #specification: Specification mining in concurrent and distributed systems (SK), pp. 1086–1089.
ICSE-2011-Kumar11a #concurrent #distributed #specification: Specification mining in concurrent and distributed systems (SK), pp. 1161–1163.
ICSE-2011-KumarKRL #graph #sequence: Mining message sequence graphs (SK, SCK, AR, DL), pp. 91–100.
ICSE-2011-LeeCR #parametricity #specification: Mining parametric specifications (CL, FC, GR), pp. 591–600.
ICSE-2011-PortNHH #case study #development #experience #scalability: Experiences with text mining large collections of unstructured systems development artifacts at jpl (DP, APN, JH, LH), pp. 701–710.
ICSE-2011-TanZP #concurrent #debugging #detection #named: aComment: mining annotations from comments and code to detect interrupt related concurrency bugs (LT, YZ, YP), pp. 11–20.
ICSE-2011-Thomas #modelling #repository #topic #using: Mining software repositories using topic models (SWT), pp. 1138–1139.
SAC-2011-AhluwaliaGCY #privacy: Target-based privacy preserving association rule mining (MA, AG, ZC, YY), pp. 962–967.
SAC-2011-BanZATK: Mining interlacing manifolds in high dimensional spaces (TB, CZ, SA, TT, YK), pp. 942–949.
SAC-2011-CuzzocreaS #clustering #database #framework #named: ClustCube: an OLAP-based framework for clustering and mining complex database objects (AC, PS), pp. 976–982.
SAC-2011-Fournier-VigerNT #named #sequence: RuleGrowth: mining sequential rules common to several sequences by pattern-growth (PFV, RN, VSMT), pp. 956–961.
SAC-2011-KadriE #nondeterminism #sequence #web: Mining uncertain web log sequences with access history probabilities (OK, CIE), pp. 1059–1060.
SAC-2011-LeungJ #data type #nondeterminism #using: Frequent itemset mining of uncertain data streams using the damped window model (CKSL, FJ), pp. 950–955.
SAC-2011-LeungS #equivalence #nondeterminism: Equivalence class transformation based mining of frequent itemsets from uncertain data (CKSL, LS), pp. 983–984.
SAC-2011-Perez-CastilloGPWP #comparison #empirical #process: An empirical comparison of static and dynamic business process mining (RPC, IGRdG, MP, BW, ÁSP), pp. 272–279.
CASE-2011-JamesBHACC #mobile #using: Tele-operation of a mobile mining robot using a panoramic display: an exploration of operators sense of presence (CAJ, TPB, KH, LA, CC, AC), pp. 279–284.
HPDC-2011-BalkirFR #architecture #distributed #pipes and filters #using: A distributed look-up architecture for text mining applications using mapreduce (ASB, ITF, AR), pp. 279–280.
PDP-2011-CesarioT #data mining #distributed #framework #grid: A Failure Handling Framework for Distributed Data Mining Services on the Grid (EC, DT), pp. 70–79.
PDP-2011-SaenkoK #algorithm #problem #search-based: Genetic Algorithms for Role Mining Problem (IS, IVK), pp. 646–650.
ECSA-2010-KamalA #design pattern: Mining Relationships between the Participants of Architectural Patterns (AWK, PA), pp. 401–408.
SIGMOD-2010-HanSYY #analysis #approach #database #network: Mining knowledge from databases: an information network analysis approach (JH, YS, XY, PSY), pp. 1251–1252.
SIGMOD-2010-KhanYW #graph #proximity #scalability #towards: Towards proximity pattern mining in large graphs (AK, XY, KLW), pp. 867–878.
SIGMOD-2010-LiJLTYHK #database #named: MoveMine: mining moving object databases (ZL, MJ, JGL, LAT, YY, JH, RK), pp. 1203–1206.
SIGMOD-2010-OrdonezG #data mining #database #research: Database systems research on data mining (CO, JGG), pp. 1253–1254.
SIGMOD-2010-ParameswaranKBG #algorithm #named #precedence #recommendation: Recsplorer: recommendation algorithms based on precedence mining (AGP, GK, BB, HGM), pp. 87–98.
VLDB-2010-AggarwalLYJ #graph #on the: On Dense Pattern Mining in Graph Streams (CCA, YL, PSY, RJ), pp. 975–984.
VLDB-2010-BedathurBDMW #ad hoc: Interesting-Phrase Mining for Ad-Hoc Text Analytics (SJB, KB, JD, NM, GW), pp. 1348–1357.
VLDB-2010-CaoCJ10a #semantics: Mining Significant Semantic Locations From GPS Data (XC, GC, CSJ), pp. 1009–1020.
VLDB-2010-LiDHK #clustering #named: Swarm: Mining Relaxed Temporal Moving Object Clusters (ZL, BD, JH, RK), pp. 723–734.
VLDB-2010-Muthukrishnan #data transformation #internet: Data Management and Mining in Internet Ad Systems (SM), pp. 1655–1656.
VLDB-2010-RenzCK #database #nondeterminism #similarity: Similarity Search and Mining in Uncertain Databases (MR, RC, HPK, AZ, TB), pp. 1653–1654.
EDM-2010-BernauerP #data mining #student: Data Mining of both Right and Wrong Answers from a Mathematics and a Science M/C Test given Collectively to 11, 228 Students from India in years 4, 6 and 8 (JB, JP), pp. 273–274.
EDM-2010-DMelloG #experience #learning: Mining Bodily Patterns of Affective Experience during Learning (SKD, ACG), pp. 31–40.
EDM-2010-DominguezYC #data mining #generative #python: Data Mining for Generating Hints in a Python Tutor (AKD, KY, JRC), pp. 91–100.
EDM-2010-FalakmasirH #data mining #education #using: Using Educational Data Mining Methods to Study the Impact of Virtual Classroom in E-Learning (MHF, JH), pp. 241–248.
EDM-2010-HowardJN #process #using: Examining Learner Control in a Structured Inquiry Cycle Using Process Mining (LH, JJ, CN), pp. 71–80.
EDM-2010-KrugerMW #analysis #education: A Data Model to Ease Analysis and Mining of Educational Data (AK, AM, BW), pp. 131–140.
EDM-2010-KrugerMW10a #data analysis #data mining: When Data Exploration and Data Mining meet while Analysing Usage Data of a Course (AK, AM, BW), pp. 305–306.
EDM-2010-Rajibussalim #interactive #learning #student: Mining Students’ Interaction Data from a System that Support Learning by Reflection (R), pp. 249–256.
EDM-2010-RomeroRLV: Mining Rare Association Rules from e-Learning Data (CR, JRR, JML, SV), pp. 171–180.
EDM-2010-RomeroVVP #student #testing: Class Association Rules Mining from Students’ Test Data (CR, SV, EV, MP), pp. 317–318.
EDM-2010-SouthavilayYC #collaboration #process #student: Process Mining to Support Students’ Collaborative Writing (VS, KY, RAC), pp. 257–266.
EDM-2010-SrinivasBG: Mining information from tutor data to improve pedagogical content knowledge (SS, MB, AG), pp. 275–276.
EDM-2010-VialardiCBVEPO #case study #data mining #student: A Case Study: Data Mining Applied to Student Enrollment (CVS, JC, AB, DV, JE, JPP, AO), pp. 333–334.
EDM-2010-XiongLS #locality #performance #problem: Assessing Reviewer’s Performance Based on Mining Problem Localization in Peer-Review Data (WX, DJL, CDS), pp. 211–220.
ICPC-2010-RevelleDP #data fusion #feature model #using #web: Using Data Fusion and Web Mining to Support Feature Location in Software (MR, BD, DP), pp. 14–23.
MSR-2010-BruchMM #framework #reuse #subclass: Mining subclassing directives to improve framework reuse (MB, MM, MM), pp. 141–150.
MSR-2010-GegickRX #case study #debugging #identification #industrial #security: Identifying security bug reports via text mining: An industrial case study (MG, PR, TX), pp. 11–20.
MSR-2010-Herbsleb #named #question: MSR: Mining for scientific results? (JDH).
MSR-2010-HindleHSJ #challenge #gnome: Mining Challenge 2010: FreeBSD, GNOME Desktop and Debian/Ubuntu (AH, IH, ES, ZMJ), pp. 82–85.
MSR-2010-MauczkaSFBG #security: Mining security changes in FreeBSD (AM, CS, FF, MB, TG), pp. 90–93.
MSR-2010-NagappanV: Abstracting log lines to log event types for mining software system logs (MN, MAV), pp. 114–117.
MSR-2010-NussbaumZ #assurance #data mining #database #metadata #quality: The Ultimate Debian Database: Consolidating bazaar metadata for Quality Assurance and data mining (LN, SZ), pp. 52–61.
MSR-2010-PosnettBD #java #named: THEX: Mining metapatterns from java (DP, CB, PTD), pp. 122–125.
MSR-2010-Robles #case study #repository: Replicating MSR: A study of the potential replicability of papers published in the Mining Software Repositories proceedings (GR), pp. 171–180.
MSR-2010-VetroTM #java #precise: Assessing the precision of FindBugs by mining Java projects developed at a university (AV, MT, MM), pp. 110–113.
SCAM-2010-Zeller #in the large #learning #modelling: Learning from 6,000 Projects: Mining Models in the Large (AZ), pp. 3–6.
WCRE-2010-LozanoKMA #source code: Mining Source Code for Structural Regularities (AL, AK, KM, GA), pp. 22–31.
WCRE-2010-SurianLL #collaboration #developer #network #scalability: Mining Collaboration Patterns from a Large Developer Network (DS, DL, EPL), pp. 269–273.
FDG-2010-LewisW #case study #game studies #statistics #web #web service: Mining game statistics from web services: a World of Warcraft armory case study (CL0, NWF), pp. 100–107.
CSCW-2010-GuyJPRU #people #similarity #social #social media: Same places, same things, same people?: mining user similarity on social media (IG, MJ, AP, IR, EU), pp. 41–50.
CAiSE-2010-AalstPS #process: Beyond Process Mining: From the Past to Present and Future (WMPvdA, MP, MS), pp. 38–52.
EDOC-2010-KalsingNIT #approach #incremental #legacy #process: An Incremental Process Mining Approach to Extract Knowledge from Legacy Systems (AK, GSdN, CI, LHT), pp. 79–88.
ICEIS-AIDSS-2010-BenayadiG #framework #sequence: Mining Timed Sequences with TOM4L Framework (NB, MLG), pp. 111–120.
ICEIS-AIDSS-2010-CarvalhoSP #data mining: Swarm Intelligence for Rule Discovery in Data Mining (ABdC, TS, AP), pp. 314–319.
ICEIS-AIDSS-2010-CuzzocreaFP #abstraction #analysis #collaboration #effectiveness #flexibility #process: Effective Analysis of Flexible Collaboration Processes by Way of Abstraction and Mining Techniques (AC, FF, LP), pp. 157–166.
ICEIS-AIDSS-2010-Vilas-BoasSPSR #data mining #predict: Hourly Prediction of Organ Failure and Outcome in Intensive Care based on Data Mining Techniques (MVB, MFS, FP, ÁMS, FR), pp. 270–277.
ICEIS-DISI-2010-KalsingTI #algorithm #incremental #process: An Incremental Process Mining Algorithm (AK, LHT, CI), pp. 263–268.
ICEIS-DISI-2010-ZhangOCK #case study #data mining #education #student: Use Data Mining to Improve Student Retention in Higher Education — A Case Study (YZ, SO, TC, HK), pp. 190–197.
ICEIS-ISAS-2010-EliceguiVM #data mining #semantics: Combining Semantic Technologies and Data Mining to Endow BSS/OSS Systems with Intelligence — Particularization to an International Telecom Company Tariff System (JME, GTdV, MdFM), pp. 350–355.
ICEIS-ISAS-2010-KikuchiMAM #process: Process Mining for Job Nets in Integrated Complex Computer Systems (SK, YM, MA, SM), pp. 5–12.
ICEIS-J-2010-KikuchiMAM10a #enterprise #process: Process Mining for Job Nets in Integrated Enterprise Systems (SK, YM, MA, SM), pp. 299–310.
CIKM-2010-BingSJZL #documentation #learning #ontology #representation: Learning ontology resolution for document representation and its applications in text mining (LB, BS, SJ, YZ, WL), pp. 1713–1716.
CIKM-2010-CaoBYCT #approach #effectiveness #mobile: An effective approach for mining mobile user habits (HC, TB, QY, EC, JT), pp. 1677–1680.
CIKM-2010-ChenJPL #algorithm #database #performance #scalability: An efficient algorithm for mining time interval-based patterns in large database (YCC, JCJ, WCP, SYL), pp. 49–58.
CIKM-2010-FlorezD #process: Mining rules to explain activities in videos (OUF, CED), pp. 1577–1580.
CIKM-2010-GaoYW #multi #named #query: SEQUEL: query completion via pattern mining on multi-column structural data (CG, QY, JW), pp. 1955–1956.
CIKM-2010-GodboleBGV #repository #taxonomy: Building re-usable dictionary repositories for real-world text mining (SG, IB, AG, AV), pp. 1189–1198.
CIKM-2010-GuoZGZS #analysis #named: OpinionIt: a text mining system for cross-lingual opinion analysis (HG, HZ, ZG, XZ, ZS), pp. 1199–1208.
CIKM-2010-LeungLLW #network #social: Mining interesting link formation rules in social networks (CWkL, EPL, DL, JW), pp. 209–218.
CIKM-2010-LiuTHJY #network #topic: Mining topic-level influence in heterogeneous networks (LL, JT, JH, MJ, SY), pp. 199–208.
CIKM-2010-MoghaddamE: Opinion digger: an unsupervised opinion miner from unstructured product reviews (SM, ME), pp. 1825–1828.
CIKM-2010-SeseSF #network: Mining networks with shared items (JS, MS, MF), pp. 1681–1684.
CIKM-2010-WangCLC #approach #modelling #probability: Accelerating probabilistic frequent itemset mining: a model-based approach (LW, RC, SDL, DWLC), pp. 429–438.
CIKM-2010-WangJL #collaboration #process: Collaboration analytics: mining work patterns from collaboration activities (QW, HJ, YL), pp. 1861–1864.
CIKM-2010-ZhangSZBA #documentation #named #parallel #probability #topic: PTM: probabilistic topic mapping model for mining parallel document collections (DZ, JS, CZ, AB, NA), pp. 1653–1656.
CIKM-2010-ZhouLBXL #information management #reasoning #set: Rough sets based reasoning and pattern mining for a two-stage information filtering system (XZ, YL, PB, YX, RYKL), pp. 1429–1432.
CIKM-2010-ZhuangLSHXSX #classification #collaboration #multi: Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification (FZ, PL, ZS, QH, YX, ZS, HX), pp. 359–368.
ECIR-2010-DaiD #retrieval #roadmap: Mining Anchor Text Trends for Retrieval (ND, BDD), pp. 127–139.
ECIR-2010-DaiDW #topic: Mining Neighbors’ Topicality to Better Control Authority Flow (ND, BDD, YW), pp. 653–657.
ECIR-2010-Shi #information retrieval #web: Mining OOV Translations from Mixed-Language Web Pages for Cross Language Information Retrieval (LS), pp. 471–482.
ICML-2010-DasguptaN #clustering: Mining Clustering Dimensions (SD, VN), pp. 263–270.
ICML-2010-XuHFPJ #detection #problem #scalability: Detecting Large-Scale System Problems by Mining Console Logs (WX, LH, AF, DAP, MIJ), pp. 37–46.
ICPR-2010-Artigas-FuentesGB #approximate #similarity: A High-Dimensional Access Method for Approximated Similarity Search in Text Mining (FJAF, RGG, JMBC), pp. 3155–3158.
ICPR-2010-XiaLH #modelling #using: Mining Exemplars for Object Modelling Using Affinity Propagation (SX, JL, ERH), pp. 918–921.
KDD-2010-Feldman #data mining #lessons learnt #quantifier #scalability: The quantification of advertising: (+ lessons from building businesses based on large scale data mining) (KF), pp. 5–6.
KDD-2010-FriedmanS #data mining #difference #privacy: Data mining with differential privacy (AF, AS), pp. 493–502.
KDD-2010-GaoW #nondeterminism: Direct mining of discriminative patterns for classifying uncertain data (CG, JW), pp. 861–870.
KDD-2010-HendersonEFALMPT #approach #forensics #graph #metric #multi: Metric forensics: a multi-level approach for mining volatile graphs (KH, TER, CF, LA, LL, KM, BAP, HT), pp. 163–172.
KDD-2010-KarguptaGF #data mining #generative: The next generation of transportation systems, greenhouse emissions, and data mining (HK, JG, WF), pp. 1209–1212.
KDD-2010-KarguptaSG #data mining #distributed #overview #performance: MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system (HK, KS, MG), pp. 37–46.
KDD-2010-KumarGM #data mining #fault #health #predict: Data mining to predict and prevent errors in health insurance claims processing (MK, RG, ZSM), pp. 65–74.
KDD-2010-LamC #data type #flexibility: Mining top-k frequent items in a data stream with flexible sliding windows (HTL, TC), pp. 283–292.
KDD-2010-LiAZ: Mining positive and negative patterns for relevance feature discovery (YL, AA, NZ), pp. 753–762.
KDD-2010-LiDHKN #behaviour: Mining periodic behaviors for moving objects (ZL, BD, JH, RK, PN), pp. 1099–1108.
KDD-2010-LouFYLW #workflow: Mining program workflow from interleaved traces (JGL, QF, SY, JL, BW), pp. 613–622.
KDD-2010-Lu #data mining #industrial #online: Data mining in the online services industry (QL), pp. 1–2.
KDD-2010-MaxwellBR #graph #memory management #using: Diagnosing memory leaks using graph mining on heap dumps (EKM, GB, NR), pp. 115–124.
KDD-2010-Ruggieri: Frequent regular itemset mining (SR), pp. 263–272.
KDD-2010-SunCCC #nondeterminism #probability: Mining uncertain data with probabilistic guarantees (LS, RC, DWC, JC), pp. 273–282.
KDD-2010-TaiYC #outsourcing #pseudo #taxonomy: k-Support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining (CHT, PSY, MSC), pp. 473–482.
KDD-2010-TsengWSY #algorithm #named #performance: UP-Growth: an efficient algorithm for high utility itemset mining (VST, CWW, BES, PSY), pp. 253–262.
KDD-2010-WangCSX #algorithm #mobile #network #social: Community-based greedy algorithm for mining top-K influential nodes in mobile social networks (YW, GC, GS, KX), pp. 1039–1048.
KDD-2010-WangHJTZYG #network #research: Mining advisor-advisee relationships from research publication networks (CW, JH, YJ, JT, DZ, YY, JG), pp. 203–212.
KDD-2010-YangNSS #data mining #privacy: Collusion-resistant privacy-preserving data mining (BY, HN, IS, JS), pp. 483–492.
KDD-2010-ZhengSTLLCH #data mining #network #using: Using data mining techniques to address critical information exchange needs in disaster affected public-private networks (LZ, CS, LT, TL, SL, SCC, VH), pp. 125–134.
KDIR-2010-AchaKV #analysis #data mining #modelling: Tactical Analysis Modeling through Data Mining — Pattern Discovery in Racket Sports (ATA, WAK, JKV), pp. 176–181.
KDIR-2010-CarulloB #analysis #machine learning #web: Machine Learning and Link Analysis for Web Content Mining (MC, EB), pp. 156–161.
KDIR-2010-CorreiaCL #architecture #collaboration #data mining: An Architecture for Collaborative Data Mining (FC, RC, JCL), pp. 467–470.
KDIR-2010-Ghosh #locality #modelling #multi #predict #scalability #using: Actionable Mining of Large, Multi-relational Data using Localized Predictive Models (JG), pp. 9–10.
KDIR-2010-Rauch #data mining #logic #semantics #web: Logic of Discovery, Data Mining and Semantic Web — Position Paper (JR), pp. 342–351.
KDIR-2010-Seifert #knowledge-based #music: Knowledge-based Mining of Patterns and Structure of Symbolic Music Files (FS0), pp. 358–363.
KDIR-2010-Vazquez-RodriguezPGFC #data mining #visual notation: A New Visual Data Mining Tool for gvSIG GIS (RVR, CPR, IYGH, AFM, JCTC), pp. 428–431.
SEKE-2010-SilvaS #classification #data mining #knowledge base #modelling #relational #testing: Modeling and Testing a Knowledge Base for Instructing Users to Choose the Classification Task in Relational Data Mining (LMdS, AEAdS), pp. 608–613.
SIGIR-2010-FengWZM #image #scalability #video: Mining adjacent markets from a large-scale ads video collection for image advertising (GF, XJW, LZ, WYM), pp. 893–894.
SIGIR-2010-JiangPL #challenge #information retrieval #web: Search and browse log mining for web information retrieval: challenges, methods, and applications (DJ, JP, HL), p. 912.
SIGIR-2010-LeeJSL #identification: Mining the blogosphere for top news stories identification (YL, HYJ, WS, JHL), pp. 395–402.
SPLC-2010-YoshimuraAF #constraints #feature model #identification: A Method to Identify Feature Constraints Based on Feature Selections Mining (KY, YA, TF), pp. 425–429.
ASE-2010-GibiecCC #query #towards: Towards mining replacement queries for hard-to-retrieve traces (MG, AC, JCH), pp. 245–254.
ASE-2010-HuangPWXM #assurance: Text mining in supporting software systems risk assurance (LH, DP, LW, TX, TM), pp. 163–166.
ASE-2010-LoM #specification: Scenario-based and value-based specification mining: better together (DL, SM), pp. 387–396.
ASE-2010-ShangAH #case study #experience #pipes and filters #repository #scalability #tool support #using: An experience report on scaling tools for mining software repositories using MapReduce (WS, BA, AEH), pp. 275–284.
ASE-2010-SindhgattaNSVR #developer: Timesheet assistant: mining and reporting developer effort (RS, NCN, BS, KV, AGR), pp. 265–274.
ICSE-2010-DoanLMK #named #specification: LM: a miner for scenario-based specifications (TAD, DL, SM, SCK), pp. 319–320.
ICSE-2010-HassanX #re-engineering: Mining software engineering data (AEH, TX), pp. 503–504.
ICSE-2010-ZhongTXZW #api #migration: Mining API mapping for language migration (HZ, ST, TX, LZ, QW), pp. 195–204.
SAC-2010-BaralisCC #dataset #persistent #scalability: A persistent HY-Tree to efficiently support itemset mining on large datasets (EB, TC, SC), pp. 1060–1064.
SAC-2010-BlundoC #algorithm: A simple role mining algorithm (CB, SC), pp. 1958–1962.
SAC-2010-CeciALM #approach #data mining #ranking #relational: Complex objects ranking: a relational data mining approach (MC, AA, CL, DM), pp. 1071–1077.
SAC-2010-ChengSMZ #data mining #database #integration #named #online: PROM-OOGLE: data mining and integration of on-line databases to discover gene promoters (DC, JS, MMP, ORZ), pp. 1547–1551.
SAC-2010-CostaFGMO #learning #modelling: Mining models of exceptional objects through rule learning (GC, FF, MG, GM, RO), pp. 1078–1082.
SAC-2010-FlouvatSGRG: Constrained colocation mining: application to soil erosion characterization (FF, NSF, DG, IR, CG), pp. 1054–1059.
SAC-2010-GoethalsPM #database #relational #set: Mining interesting sets and rules in relational databases (BG, WLP, MM), pp. 997–1001.
SAC-2010-Kaneiwa #approach #information management #set: A rough set approach to mining connections from information systems (KK), pp. 990–996.
SAC-2010-KatevaLRSTR #architecture #data mining: SE-155 DBSA: a device-based software architecture for data mining (JK, PL, TR, JS, LT, JR), pp. 2273–2280.
SAC-2010-LeungHB #constraints #nondeterminism: Mining uncertain data for frequent itemsets that satisfy aggregate constraints (CKSL, BH, DAB), pp. 1034–1038.
SAC-2010-LiuJWZQ: Mining preorder relation between knowledge units from text (JL, LJ, ZW, QZ, YnQ), pp. 1047–1053.
SAC-2010-LuccheseOP #dataset #generative: A generative pattern model for mining binary datasets (CL, SO, RP), pp. 1109–1110.
SAC-2010-MarinhoCDFBBL #data mining #education #framework #ontology: An ontology-based software framework to provide educational data mining (TM, EdBC, DD, RF, LMB, IIB, HPLL), pp. 1433–1437.
SAC-2010-MengleG #category theory: Mining temporal relationships among categories (SSRM, NG), pp. 1107–1108.
SAC-2010-NingYPM #named #visualisation: OncoViz: a user-centric mining and visualization tool for cancer-related literature (ZN, JSY, MJP, AMM), pp. 1827–1828.
SAC-2010-RomaniAZCTT #algorithm #named: CLEARMiner: a new algorithm for mining association patterns on heterogeneous time series from climate data (LASR, AMHdÁ, JZJ, RC, CTJ, AJMT), pp. 900–905.
SAC-2010-SamiYPHH #api #detection: Malware detection based on mining API calls (AS, BY, HR, NP, SH, AH), pp. 1020–1025.
SAC-2010-ShieTY #data type #online: Online mining of temporal maximal utility itemsets from data streams (BES, VST, PSY), pp. 1622–1626.
CC-2010-JockschMSGA #compilation: Mining Opportunities for Code Improvement in a Just-In-Time Compiler (AJ, MM, JS, NG, JNA), pp. 10–25.
DAC-2010-LiFS #scalability #specification #verification: Scalable specification mining for verification and diagnosis (WL, AF, SAS), pp. 755–760.
DATE-2010-VasudevanSPTTJ #automation #data mining #generative #named #static analysis #using: GoldMine: Automatic assertion generation using data mining and static analysis (SV, DS, SJP, DT, WT, DRJ), pp. 626–629.
HPDC-2010-HoblitzellMYFXB #biology: Text mining for bone biology (AH, SM, QY, SF, YX, JB), pp. 522–530.
PDP-2010-KomashinskiyK #data mining #detection: Malware Detection by Data Mining Techniques Based on Positionally Dependent Features (DK, IVK), pp. 617–623.
ISSTA-2010-DallmeierKMHZ #generative #specification #testing: Generating test cases for specification mining (VD, NK, CM, SH, AZ), pp. 85–96.
TAP-2010-ThummalapentaHTW #automation #generative #named #testing: DyGen: Automatic Generation of High-Coverage Tests via Mining Gigabytes of Dynamic Traces (ST, JdH, NT, SW), pp. 77–93.
ECDL-2009-ChenRB #how #online #people #visualisation #web: How People Read Books Online: Mining and Visualizing Web Logs for Use Information (RC, AR, BBB), pp. 364–369.
ICDAR-2009-KizuYTGS #2d #data mining: 2D CAD Data Mining Based on Spatial Relation (HK, JY, TT, KG, NS), pp. 326–330.
SIGMOD-2009-WangYGYTWLP #case study #communication #data mining #mobile #named: MobileMiner: a real world case study of data mining in mobile communication (TW, BY, JG, DY, ST, HW, KL, JP), pp. 1083–1086.
VLDB-2009-ChaudhuriGX #approximate #documentation: Mining Document Collections to Facilitate Accurate Approximate Entity Matching (SC, VG, DX), pp. 395–406.
VLDB-2009-ChenBN #evolution #maintenance #named #performance #web: NEAR-Miner: Mining Evolution Associations of Web Site Directories for Efficient Maintenance of Web Archives (LC, SSB, WN), pp. 1150–1161.
VLDB-2009-ChenLFCYH #graph #random #summary: Mining Graph Patterns Efficiently via Randomized Summaries (CC, CXL, MF, MC, XY, JH), pp. 742–753.
VLDB-2009-LeglerLSK #distributed #robust #using: Robust Distributed Top-N Frequent Pattern Mining Using the SAP BW Accelerator (TL, WL, JS, JK), pp. 1438–1449.
VLDB-2009-TatikondaP #manycore: Mining Tree-Structured Data on Multicore Systems (ST, SP), pp. 694–705.
VLDB-2009-WongCHKM #outsourcing: An Audit Environment for Outsourcing of Frequent Itemset Mining (WKW, DWLC, EH, BK, NM), pp. 1162–1172.
VLDB-2009-YangRW #execution #multi #streaming: A Shared Execution Strategy for Multiple Pattern Mining Requests over Streaming Data (DY, EAR, MOW), pp. 874–885.
EDM-2009-AnayaB #approach #collaboration #data mining #framework: A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks (ARA, JB), pp. 210–219.
EDM-2009-PechenizkiyTVAB #assessment #online #process: Process Mining Online Assessment Data (MP, NT, EV, WMPvdA, PDB), pp. 279–288.
EDM-2009-RomeroVGCG #collaboration #data mining #education: Collaborative Data Mining Tool for Education (CR, SV, EG, CdC, MG), pp. 299–308.
EDM-2009-SacinASO #data mining #education #recommendation #using: Recommendation in Higher Education Using Data Mining Techniques (CVS, JBA, LS, AO), pp. 191–199.
ICSM-2009-HuangSWSW #industrial #legacy #preprocessor: Preprocessing the noise in legacy user permission assignment data for role mining — An industrial practice (CH, JS, XW, YS, DW), pp. 403–406.
ICSM-2009-Zimmermann #debugging #development #predict #process: Changes and bugs — Mining and predicting development activities (TZ), pp. 443–446.
MSR-2009-AnbalaganV #on the #repository: On mining data across software repositories (PA, MAV), pp. 171–174.
MSR-2009-BajracharyaL #code search #topic: Mining search topics from a code search engine usage log (SKB, CVL), pp. 111–120.
MSR-2009-BirdRBHGD #git: The promises and perils of mining git (CB, PCR, ETB, DJH, DMG, PTD), pp. 1–10.
MSR-2009-EnslenHPV #analysis #automation #identifier #source code: Mining source code to automatically split identifiers for software analysis (EE, EH, LLP, KVS), pp. 71–80.
MSR-2009-HattoriL: Mining the history of synchronous changes to refine code ownership (LH, ML), pp. 141–150.
MSR-2009-HerzigZ #challenge #repository: Mining the Jazz repository: Challenges and opportunities (KH, AZ), pp. 159–162.
MSR-2009-LinsteadB #debugging #gnome #modelling #statistics #topic: Mining the coherence of GNOME bug reports with statistical topic models (EL, PB), pp. 99–102.
MSR-2009-ShangJAH #framework #pipes and filters #repository #research: MapReduce as a general framework to support research in Mining Software Repositories (MSR) (WS, ZMJ, BA, AEH), pp. 21–30.
WCRE-1999-LoRRV99a #algorithm #evaluation #quantifier: Mining Quantified Temporal Rules: Formalism, Algorithms, and Evaluation (DL, GR, VPR, KV), pp. 62–71.
CIG-2009-WeberM #approach #data mining #predict: A data mining approach to strategy prediction (BGW, MM), pp. 140–147.
DHM-2009-NamA #data mining #image: Data Mining of Image Segments Data with Reduced Neurofuzzy System (DHN, EA), pp. 710–716.
DHM-2009-PanCL #adaptation #behaviour #online #user interface: User Behavior Mining for On-Line GUI Adaptation (WP, YC, JL), pp. 275–284.
HCI-NT-2009-TogawaKY #communication #detection #peer-to-peer #visualisation: Peer-to-Peer File Sharing Communication Detection System with Traffic Mining and Visualization (ST, KK, YY), pp. 900–909.
HIMI-DIE-2009-HorvathLK #analysis #approach #data mining #usability: Usability Analyses of CRM Systems in Call Centers: The Data Mining Approach (ÁH, LL, AK), pp. 40–48.
HIMI-II-2009-SagaTT #analysis #named: Loopo: Integrated Text Miner for FACT-Graph-Based Trend Analysis (RS, HT, KT), pp. 192–200.
ICEIS-AIDSS-2009-Antunes: Mining Patterns in the Presence of Domain Knowledge (CA), pp. 188–193.
ICEIS-AIDSS-2009-BiscarriMLGBM #detection #framework: A Mining Framework to Detect Non-technical Losses in Power Utilities (FB, IM, CL, JIG, JB, RM), pp. 96–101.
ICEIS-AIDSS-2009-BratuP #data mining #preprocessor #towards: Towards a Unified Strategy for the Preprocessing Step in Data Mining (CVB, RP), pp. 230–235.
ICEIS-AIDSS-2009-ChenC #data mining: The Role of Data Mining Techniques in Emergency Management (NC, AC), pp. 118–123.
ICEIS-AIDSS-2009-Jou #algorithm #hybrid: A Projection-based Hybrid Sequential Patterns Mining Algorithm (CJ), pp. 152–157.
ICEIS-AIDSS-2009-MarinicaOG #algorithm #using: User-driven Association Rule Mining using a Local Algorithm (CM, AO, FG), pp. 200–205.
ICEIS-ISAS-2009-Petrusel #modelling #process #workflow: Mining and Modeling Decision Workflows from DSS User Activity Logs (RP), pp. 144–149.
ICEIS-ISAS-2009-TatsiopoulosB #ontology: Ontology Mapping based on Association Rule Mining (CT, BB), pp. 33–40.
ICEIS-J-2009-CunhaAM #data mining #reuse: Knowledge Reuse in Data Mining Projects and Its Practical Applications (RCLVC, PJLA, SRdLM), pp. 317–324.
ICEIS-J-2009-FritzscheML #analysis #concept #data mining #design #industrial #interactive #quality: Interactive Quality Analysis in the Automotive Industry: Concept and Design of an Interactive, Web-Based Data Mining Application (SF, MM, CL), pp. 402–414.
ICEIS-J-2009-MianiYSB #algorithm #fuzzy #ontology: NARFO Algorithm: Mining Non-redundant and Generalized Association Rules Based on Fuzzy Ontologies (RGM, CAY, MTPS, MB), pp. 415–426.
CIKM-2009-ChenPBSM #data mining #exclamation #lessons learnt: Practical lessons of data mining at Yahoo! (YC, DP, PB, AS, AM), pp. 1047–1056.
CIKM-2009-ChokG #framework #network #realtime: Spatio-temporal association rule mining framework for real-time sensor network applications (HC, LG), pp. 1761–1764.
CIKM-2009-GuoR #interactive #query: Mining linguistic cues for query expansion: applications to drug interaction search (SG, NR), pp. 335–344.
CIKM-2009-GwaderaC #ranking #using: Mining and ranking streams of news stories using cross-stream sequential patterns (RG, FC), pp. 1709–1712.
CIKM-2009-KasneciEW #named: MING: mining informative entity relationship subgraphs (GK, SE, GW), pp. 1653–1656.
CIKM-2009-MabroukehE #ontology #predict #semantics #using #web: Using domain ontology for semantic web usage mining and next page prediction (NRM, CIE), pp. 1677–1680.
CIKM-2009-PitonBBG #data mining: Domain driven data mining to improve promotional campaign ROI and select marketing channels (TP, JB, HB, FG), pp. 1057–1066.
CIKM-2009-PopescuGM: Mining tourist information from user-supplied collections (AP, GG, PAM), pp. 1713–1716.
CIKM-2009-SahlgrenK #social #social media: Terminology mining in social media (MS, JK), pp. 405–414.
CIKM-2009-Shi #adaptation #information retrieval #web: Adaptive web mining of bilingual lexicons for cross language information retrieval (LS), pp. 1561–1564.
CIKM-2009-SunMG #graph #independence #information retrieval: Independent informative subgraph mining for graph information retrieval (BS, PM, CLG), pp. 563–572.
CIKM-2009-TaoO #data type: Mining data streams with periodically changing distributions (YT, MTÖ), pp. 887–896.
CIKM-2009-TaoO09a #data type: Mining frequent itemsets in time-varying data streams (YT, MTÖ), pp. 1521–1524.
CIKM-2009-ZhangYWGGBYS #documentation #named #social #web: sDoc: exploring social wisdom for document enhancement in web mining (XZ, LY, XW, HG, ZG, SB, YY, ZS), pp. 395–404.
CIKM-2009-ZouLGZ #graph #nondeterminism: Frequent subgraph pattern mining on uncertain graph data (ZZ, JL, HG, SZ), pp. 583–592.
ECIR-2009-OrlandoS #query: Mining Query Logs (SO, FS), pp. 814–817.
ECIR-2009-UdupaSBB #information retrieval #query #quote: “They Are Out There, If You Know Where to Look”: Mining Transliterations of OOV Query Terms for Cross-Language Information Retrieval (RU, KS, AB, AB), pp. 437–448.
KDD-2009-AggarwalLWW #nondeterminism: Frequent pattern mining with uncertain data (CCA, YL, JW, JW), pp. 29–38.
KDD-2009-AhmedXCM #biology #modelling #topic: Structured correspondence topic models for mining captioned figures in biological literature (AA, EPX, WWC, RFM), pp. 39–48.
KDD-2009-BerlingerioPNG #data analysis #interactive #workflow: Temporal mining for interactive workflow data analysis (MB, FP, MN, FG), pp. 109–118.
KDD-2009-BerneckerKRVZ #database #nondeterminism #probability: Probabilistic frequent itemset mining in uncertain databases (TB, HPK, MR, FV, AZ), pp. 119–128.
KDD-2009-ChenLTW #adaptation #concept: Extracting discriminative concepts for domain adaptation in text mining (BC, WL, IWT, TLW), pp. 179–188.
KDD-2009-DaruruMWG #clustering #data flow #data mining #parallel #pervasive #scalability: Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data (SD, NMM, MW, JG), pp. 1115–1124.
KDD-2009-DeodharG #predict: Mining for the most certain predictions from dyadic data (MD, JG), pp. 249–258.
KDD-2009-DingLZ: Entity discovery and assignment for opinion mining applications (XD, BL, LZ), pp. 1125–1134.
KDD-2009-DuJDLT #approach #migration: Migration motif: a spatial — temporal pattern mining approach for financial markets (XD, RJ, LD, VEL, JHTJ), pp. 1135–1144.
KDD-2009-Hand #data mining #modelling #tool support: Mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools (DJH), pp. 1–2.
KDD-2009-HanhijarviOVPTM #data mining: Tell me something I don’t know: randomization strategies for iterative data mining (SH, MO, NV, KP, NT, HM), pp. 379–388.
KDD-2009-JinHS #machine learning #named #novel #web: OpinionMiner: a novel machine learning system for web opinion mining and extraction (WJ, HHH, RKS), pp. 1195–1204.
KDD-2009-Kumar #challenge #web: Mining web logs: applications and challenges (RK), pp. 3–4.
KDD-2009-Last #data mining: Improving data mining utility with projective sampling (ML), pp. 487–496.
KDD-2009-LiMPF #named #sequence #summary: DynaMMo: mining and summarization of coevolving sequences with missing values (LL, JM, NSP, CF), pp. 507–516.
KDD-2009-LoCHKS #approach #behaviour #classification #detection: Classification of software behaviors for failure detection: a discriminative pattern mining approach (DL, HC, JH, SCK, CS), pp. 557–566.
KDD-2009-Mannila #data mining: Randomization methods in data mining (HM), pp. 5–6.
KDD-2009-MaunzHK #graph #refinement #scalability #using: Large-scale graph mining using backbone refinement classes (AM, CH, SK), pp. 617–626.
KDD-2009-MonrealePTG #named #predict: WhereNext: a location predictor on trajectory pattern mining (AM, FP, RT, FG), pp. 637–646.
KDD-2009-NijssenGR #approach #constraints #correlation #programming: Correlated itemset mining in ROC space: a constraint programming approach (SN, TG, LDR), pp. 647–656.
KDD-2009-PatnaikMSR #data mining #using: Sustainable operation and management of data center chillers using temporal data mining (DP, MM, RKS, NR), pp. 1305–1314.
KDD-2009-PoernomoG09a #fault tolerance #performance #towards: Towards efficient mining of proportional fault-tolerant frequent itemsets (AKP, VG), pp. 697–706.
KDD-2009-ShenJY #matrix: Mining discrete patterns via binary matrix factorization (BHS, SJ, JY), pp. 757–766.
KDD-2009-Srivastava #data mining: Data mining at NASA: from theory to applications (ANS), pp. 7–8.
KDD-2009-SunPLCWLRY #estimation: Mining brain region connectivity for alzheimer’s disease study via sparse inverse covariance estimation (LS, RP, JL, KC, TW, JL, ER, JY), pp. 1335–1344.
KDD-2009-WangCP #aspect-oriented #query: Mining broad latent query aspects from search sessions (XW, DC, KP), pp. 867–876.
KDD-2009-XuYL #using: Named entity mining from click-through data using weakly supervised latent dirichlet allocation (GX, SHY, HL), pp. 1365–1374.
KDD-2009-YeK #data mining: Time series shapelets: a new primitive for data mining (LY, EJK), pp. 947–956.
KDD-2009-YooYLM #email #network #personalisation #social: Mining social networks for personalized email prioritization (SY, YY, FL, ICM), pp. 967–976.
KDD-2009-ZhuM #web: Mining rich session context to improve web search (GZ, GM), pp. 1037–1046.
KDD-2009-ZhuWKL: Augmenting the generalized hough transform to enable the mining of petroglyphs (QZ, XW, EJK, SHL), pp. 1057–1066.
KDIR-2009-EnguixDJ #natural language: DNA and Natural Languages — Text Mining (GBE, VD, MDJL), pp. 140–145.
KDIR-2009-FatemiPRS #concept #retrieval #semantics #using #video: Using Association Rule Mining to Enrich Semantic Concepts for Video Retrieval (NF, FP, LER, AFS), pp. 119–126.
KDIR-2009-Fernandez-FernandezG #query #taxonomy #topic: Hierarchical Taxonomy Extraction by Mining Topical Query Sessions (MFF, DGA), pp. 229–235.
KDIR-2009-PenaVP #data mining: Explorative Data Mining for the Sizing of Population Groups (IP, HLV, EP), pp. 152–159.
KDIR-2009-SaneifarBLPR: Mining for Relevant Terms from Log Files (HS, SB, AL, PP, MR), pp. 77–84.
KDIR-2009-WohrerZDB #composition #data mining #metaprogramming #optimisation #towards: Unboxing Data Mining Via Decomposition in Operators — Towards Macro Optimization and Distribution (AW, YZ, EuHD, PB), pp. 243–248.
KDIR-2009-Zhan #collaboration #data mining #privacy: Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
KEOD-2009-Zhan #collaboration #data mining #privacy: Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
KMIS-2009-Zhan #collaboration #data mining #privacy: Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
MLDM-2009-CeciALCFVM #data type #detection #relational: Relational Frequent Patterns Mining for Novelty Detection from Data Streams (MC, AA, CL, CC, FF, CV, DM), pp. 427–439.
MLDM-2009-FernandezBFM #automation #data mining: Assisting Data Mining through Automated Planning (FF, DB, SF, DMM), pp. 760–774.
MLDM-2009-KovalevPV #image: Mining Lung Shape from X-Ray Images (VK, AP, PV), pp. 554–568.
MLDM-2009-LoglisciM #multi: Mining Multiple Level Non-redundant Association Rules through Two-Fold Pruning of Redundancies (CL, DM), pp. 251–265.
MLDM-2009-MendesA #approach #natural language: Pattern Mining with Natural Language Processing: An Exploratory Approach (ACM, CA), pp. 266–279.
RecSys-2009-Tolomei #process #recommendation #web: Search the web x.0: mining and recommending web-mediated processes (GT), pp. 417–420.
SEKE-2009-AlvaresOHB #data mining #framework #preprocessor: A Framework for Trajectory Data Preprocessing for Data Mining (LOA, GO, CAH, VB), pp. 698–702.
SEKE-2009-AndresMN #realtime #testing #using: Using a Mining Frequency Patterns Model to Automate Passive Testing of Real-time Systems (CA, MGM, MN), pp. 426–431.
SEKE-2009-CellierDFR #data mining #fault #locality #named #process: DeLLIS: A Data Mining Process for Fault Localization (PC, MD, SF, OR), pp. 432–437.
SEKE-2009-VanHilstH #metric #process #repository: Mining Objective Process Metrics from Repository Data (MVH, SH), pp. 514–519.
SIGIR-2009-WongLC #adaptation #detection #information management: Mining employment market via text block detection and adaptive cross-domain information extraction (TLW, WL, BC), pp. 283–290.
SIGIR-2009-YeHL #approach #graph #multi #wiki #word: A graph-based approach to mining multilingual word associations from wikipedia (ZY, XH, HL), pp. 690–691.
SIGIR-2009-ZhangWLOJH #dependence #parsing: Mining product reviews based on shallow dependency parsing (QZ, YW, TL, MO, JJ, XH), pp. 726–727.
ECMDA-FA-2009-KublerG #approach #qvt #using: A Pattern Mining Approach Using QVT (JK, TG), pp. 50–65.
MoDELS-2009-Booch #architecture: Architectural Mining: The Other Side of the MDD (GB), p. 627.
MoDELS-2009-Booch #architecture: Architectural Mining: The Other Side of the MDD (GB), p. 627.
ECOOP-2009-ZhongXZPM #api #named #recommendation: MAPO: Mining and Recommending API Usage Patterns (HZ, TX, LZ, JP, HM), pp. 318–343.
ASE-2009-AcharyaK #health #modelling #monitoring #performance: Mining Health Models for Performance Monitoring of Services (MA, VK), pp. 409–420.
ASE-2009-LoM #specification: Mining Hierarchical Scenario-Based Specifications (DL, SM), pp. 359–370.
ASE-2009-ThummalapentaX #detection #named: Alattin: Mining Alternative Patterns for Detecting Neglected Conditions (ST, TX), pp. 283–294.
ASE-2009-WasylkowskiZ #specification: Mining Temporal Specifications from Object Usage (AW, AZ), pp. 295–306.
ESEC-FSE-2009-NguyenNPAN #graph #multi: Graph-based mining of multiple object usage patterns (TTN, HAN, NHP, JMAK, TNN), pp. 383–392.
ESEC-FSE-2009-ThummalapentaXTHS #generative #named #object-oriented #source code #testing: MSeqGen: object-oriented unit-test generation via mining source code (ST, TX, NT, JdH, WS), pp. 193–202.
ICSE-2009-ThummalapentaX #sequence: Mining exception-handling rules as sequence association rules (ST, TX), pp. 496–506.
SAC-2009-CaldersGPR #process #using: Using minimum description length for process mining (TC, CWG, MP, AR), pp. 1451–1455.
SAC-2009-EsfahaniMSU #process #using: Using process mining to business process distribution (FSE, MAAM, MNS, NIU), pp. 2140–2145.
SAC-2009-LinL #generative: Optimal candidate generation in spatial co-location mining (ZL, SL), pp. 1441–1445.
SAC-2009-LiuMYGF #corpus #probability: A sentence level probabilistic model for evolutionary theme pattern mining from news corpora (SL, YM, WGY, NG, OF), pp. 1742–1747.
SAC-2009-OwensMR #dataset: Capturing truthiness: mining truth tables in binary datasets (CCOI, TMM, NR), pp. 1467–1474.
SAC-2009-ShangLL #biology #functional #network: Mining functional associated patterns from biological network data (XS, ZL, WL), pp. 1488–1489.
PPoPP-2009-MaA #compilation #data mining #runtime: A compiler and runtime system for enabling data mining applications on gpus (WM, GA), pp. 287–288.
SOSP-2009-XuHFPJ #detection #problem #scalability: Detecting large-scale system problems by mining console logs (WX, LH, AF, DAP, MIJ), pp. 117–132.
FASE-2009-AcharyaX #api #source code #specification: Mining API Error-Handling Specifications from Source Code (MA, TX), pp. 370–384.
TACAS-2009-GouesW #specification: Specification Mining with Few False Positives (CLG, WW), pp. 292–306.
ISSTA-2009-ChengLZWY #debugging #graph #identification #using: Identifying bug signatures using discriminative graph mining (HC, DL, YZ, XW, XY), pp. 141–152.
ISSTA-2009-JiangS #automation #random testing #testing: Automatic mining of functionally equivalent code fragments via random testing (LJ, ZS), pp. 81–92.
DocEng-2008-CodocedoA #documentation #information management #repository: No mining, no meaning: relating documents across repositories with ontology-driven information extraction (VC, HA), pp. 110–118.
DRR-2008-Schomaker #word: Word mining in a sparsely labeled handwritten collection (LRBS), p. 68150.
HT-2008-KolakS #generative: Generating links by mining quotations (OK, BNS), pp. 117–126.
SIGMOD-2008-PatelHL #classification: Mining relationships among interval-based events for classification (DP, WH, MLL), pp. 393–404.
SIGMOD-2008-Ramaswamy #data mining: Extreme data mining (SR), pp. 1–2.
SIGMOD-2008-SunWYCHYZ #named #network: BibNetMiner: mining bibliographic information networks (YS, TW, ZY, HC, JH, XY, PZ), pp. 1341–1344.
SIGMOD-2008-WangPTT #named #visualisation: CSV: visualizing and mining cohesive subgraphs (NW, SP, KLT, AKHT), pp. 445–458.
SIGMOD-2008-YanCHY #graph: Mining significant graph patterns by leap search (XY, HC, JH, PSY), pp. 433–444.
VLDB-2008-Bar-YossefG #query: Mining search engine query logs via suggestion sampling (ZBY, MG), pp. 54–65.
VLDB-2008-DingTSWK #comparison #distance #metric #query: Querying and mining of time series data: experimental comparison of representations and distance measures (HD, GT, PS, XW, EJK), pp. 1542–1552.
VLDB-2008-LoK #specification: Mining patterns and rules for software specification discovery (DL, SCK), pp. 1609–1616.
VLDB-2008-ZhangPWN #correlation #higher-order: Mining non-redundant high order correlations in binary data (XZ, FP, WW, ABN), pp. 1178–1188.
EDM-2008-AbbasS #database #relational #towards: Towards Argument Mining from Relational DataBase (SA, HS), pp. 202–209.
EDM-2008-AllevatoTEP #automation #testing: Mining Data from an Automated Grading and Testing System by Adding Rich Reporting Capabilities (AA, MT, SHE, MAPQ), pp. 167–176.
EDM-2008-HubscherP #data mining: Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge (RH, SP), pp. 97–106.
EDM-2008-JeongB #behaviour #modelling #student: Mining Student Behavior Models in Learning-by-Teaching Environments (HJ, GB), pp. 127–136.
EDM-2008-PechenizkiyCVB #assessment #case study #student: Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study (MP, TC, EV, PDB), pp. 187–191.
EDM-2008-RomeroGFV #education #visualisation: Mining and Visualizing Visited Trails in Web-Based Educational Systems (CR, SGS, MF, SV), pp. 182–186.
EDM-2008-RomeroVEH #algorithm #data mining #student: Data Mining Algorithms to Classify Students (CR, SV, PGE, CH), pp. 8–17.
EDM-2008-ZhangMDTVC: Mining Free-form Spoken Responses to Tutor Prompts (XZ, JM, ND, CT, JV, ATC), pp. 234–241.
SIGITE-2008-Kalathur #data mining #education #experience #online #student: Enriching student experience with student driven content while teaching an online data mining class (SK), pp. 125–130.
CSMR-2008-FulopFG #benchmark #design pattern #metric #tool support #towards: Towards a Benchmark for Evaluating Design Pattern Miner Tools (LJF, RF, TG), pp. 143–152.
ICPC-2008-BhattiDR #object-oriented: Aspect Mining in Procedural Object Oriented Code (MUB, SD, AR), pp. 230–235.
ICSM-2008-Lo #execution #specification: Mining specifications in diversified formats from execution traces (DL), pp. 420–423.
MSR-2008-Bernstein #data mining #how: How to learn enough data mining to be dangerous in 60 minutes (AB), pp. 77–78.
MSR-2008-HillFBSNPV #automation #maintenance #named #source code #tool support: AMAP: automatically mining abbreviation expansions in programs to enhance software maintenance tools (EH, ZPF, HB, GS, YN, LLP, KVS), pp. 79–88.
MSR-2008-LaymanNGBB #analysis #visual notation: Mining software effort data: preliminary analysis of visual studio team system data (LL, NN, SG, JB, AB), pp. 43–46.
MSR-2008-SchulerZ: Mining usage expertise from version archives (DS, TZ), pp. 121–124.
MSR-2008-ThummalapentaX #detection #framework #named #open source #repository #web: SpotWeb: detecting framework hotspots via mining open source repositories on the web (ST, TX), pp. 109–112.
PASTE-2008-LoM #modelling #specification: Specification mining of symbolic scenario-based models (DL, SM), pp. 29–35.
WCRE-2008-IshioDMI #detection #java #source code: Mining Coding Patterns to Detect Crosscutting Concerns in Java Programs (TI, HD, TM, KI), pp. 123–132.
WCRE-2008-MensKK: Pitfalls in Aspect Mining (KM, AK, JK), pp. 113–122.
ICEIS-AIDSS-2008-BiscarriMLGBM #data mining #variability: A Data Mining Method Based on the Variability of the Customer Consumption — A Special Application on Electric Utility Companies (FB, IM, CL, JIG, JB, RM), pp. 370–374.
ICEIS-AIDSS-2008-BrissonC #data mining #ontology #process: An Ontology Driven Data Mining Process (LB, MC), pp. 54–61.
ICEIS-AIDSS-2008-IngvaldsenG #process: EVS Process Miner: Incorporating Ideas from Search, ETL into Process Mining (JEI, JAG), pp. 340–347.
ICEIS-AIDSS-2008-JansLV #case study #data mining #reduction: Internal Fraud Risk Reduction — Results of a Data Mining Case Study (MJ, NL, KV), pp. 161–166.
ICEIS-AIDSS-2008-NguyenG #approach #evolution #multi: Rule Evolution Approach for Mining Multivariate Time Series Data (VAN, VG), pp. 19–26.
ICEIS-DISI-2008-Gorea #architecture #concept #data mining #modelling #named #web: DeVisa — Concepts and Architecture of a Data Mining Models Scoring and Management Web System (DG), pp. 276–281.
ICEIS-ISAS2-2008-Nikovski #concurrent #process #representation #workflow: Workflow Trees for Representation and Mining of Implicitly Concurrent Business Processes (DN), pp. 30–36.
ICEIS-ISAS2-2008-SchultK #adaptation #automation #concept #data mining #enterprise #self: Self-Adaptive Customizing with Data Mining Methods — A Concept for the Automatic Customizing of an ERP System with Data Mining Methods (RS, GK), pp. 70–75.
ICEIS-J-2008-BrissonC08a #data mining #how #process #question #semantics: How to Semantically Enhance a Data Mining Process? (LB, MC), pp. 103–116.
CIKM-2008-Agrawal #data mining: Humane data mining (RA), pp. 1–2.
CIKM-2008-AlqadahB #algorithm #clustering #effectiveness: An effective algorithm for mining 3-clusters in vertically partitioned data (FA, RB), pp. 1103–1112.
CIKM-2008-LinL #clique #performance: Fast spatial co-location mining without cliqueness checking (ZL, SL), pp. 1461–1462.
CIKM-2008-LiWT #documentation #effectiveness #taxonomy: Effective pattern taxonomy mining in text documents (YL, STW, XT), pp. 1509–1510.
CIKM-2008-LiZBXL #information management: A two-stage text mining model for information filtering (YL, XZ, PB, YX, RYKL), pp. 1023–1032.
CIKM-2008-LoekitoB #behaviour: Mining influential attributes that capture class and group contrast behaviour (EL, JB), pp. 971–980.
CIKM-2008-MaYLK #network #process #social #using: Mining social networks using heat diffusion processes for marketing candidates selection (HM, HY, MRL, IK), pp. 233–242.
CIKM-2008-MiaoLD #integration: An integration strategy for mining product features and opinions (QM, QL, RD), pp. 1369–1370.
CIKM-2008-TanbeerAJL #data type #performance: Efficient frequent pattern mining over data streams (SKT, CFA, BSJ, YKL), pp. 1447–1448.
CIKM-2008-TongSEF #performance: Fast mining of complex time-stamped events (HT, YS, TER, CF), pp. 759–768.
CIKM-2008-UdupaSKJ #corpus: Mining named entity transliteration equivalents from comparable corpora (RU, KS, AK, JJ), pp. 1423–1424.
CIKM-2008-WangZ #effectiveness #query: Mining term association patterns from search logs for effective query reformulation (XW, CZ), pp. 479–488.
ECIR-2008-Berendt #documentation #information retrieval #web: You Are a Document Too: Web Mining and IR for Next-Generation Information Literacy (BB), p. 3.
ECIR-2008-SchedlKPW #automation #information management #music #towards #web: Towards an Automatically Generated Music Information System Via Web Content Mining (MS, PK, TP, GW), pp. 585–590.
ECIR-2008-SongHRB #composition #modelling #multi #query #using: Facilitating Query Decomposition in Query Language Modeling by Association Rule Mining Using Multiple Sliding Windows (DS, QH, SMR, PB), pp. 334–345.
KDD-2008-BifetG #adaptation #data type: Mining adaptively frequent closed unlabeled rooted trees in data streams (AB, RG), pp. 34–42.
KDD-2008-BlockeelCFGPR #database #induction #prototype: An inductive database prototype based on virtual mining views (HB, TC, ÉF, BG, AP, CR), pp. 1061–1064.
KDD-2008-CaoJPHLCL #query: Context-aware query suggestion by mining click-through and session data (HC, DJ, JP, QH, ZL, EC, HL), pp. 875–883.
KDD-2008-ChoRC #data mining #identification #network: Reconstructing chemical reaction networks: data mining meets system identification (YJC, NR, YC), pp. 142–150.
KDD-2008-FanZCGYHYV #modelling: Direct mining of discriminative and essential frequent patterns via model-based search tree (WF, KZ, HC, JG, XY, JH, PSY, OV), pp. 230–238.
KDD-2008-GrossmanG #data mining #performance #using: Data mining using high performance data clouds: experimental studies using sector and sphere (RLG, YG), pp. 920–927.
KDD-2008-GuptaFFSK #algorithm #approximate #evaluation: Quantitative evaluation of approximate frequent pattern mining algorithms (RG, GF, BF, MS, VK), pp. 301–309.
KDD-2008-HwangKRZ #graph: Bridging centrality: graph mining from element level to group level (WH, TK, MR, AZ), pp. 336–344.
KDD-2008-JiangPLCH: Mining preferences from superior and inferior examples (BJ, JP, XL, DWC, JH), pp. 390–398.
KDD-2008-KotsifakosNVT #data mining #modelling #named: Pattern-Miner: integrated management and mining over data mining models (EEK, IN, YV, YT), pp. 1081–1084.
KDD-2008-LingMZS #multi #topic: Mining multi-faceted overviews of arbitrary topics in a text collection (XL, QM, CZ, BRS), pp. 497–505.
KDD-2008-PedreschiRT #data mining: Discrimination-aware data mining (DP, SR, FT), pp. 560–568.
KDD-2008-RaedtGN #constraints #programming: Constraint programming for itemset mining (LDR, TG, SN), pp. 204–212.
KDD-2008-SaigoKT #graph: Partial least squares regression for graph mining (HS, NK, KT), pp. 578–586.
KDD-2008-ShaoCTYA #performance #sequence: Efficient ticket routing by resolution sequence mining (QS, YC, ST, XY, NA), pp. 605–613.
KDD-2008-ShengPI #data mining #multi #quality #using: Get another label? improving data quality and data mining using multiple, noisy labelers (VSS, FJP, PGI), pp. 614–622.
KDD-2008-ShiehK #named: iSAX: indexing and mining terabyte sized time series (JS, EJK), pp. 623–631.
KDD-2008-TangZYLZS #named #network #social: ArnetMiner: extraction and mining of academic social networks (JT, JZ, LY, JL, LZ, ZS), pp. 990–998.
KDD-2008-TongPSYF #graph #named #performance #scalability: Colibri: fast mining of large static and dynamic graphs (HT, SP, JS, PSY, CF), pp. 686–694.
KDD-2008-ZhangZS #categorisation #concept #data type: Categorizing and mining concept drifting data streams (PZ, XZ, YS), pp. 812–820.
RecSys-2008-ShaniCM #recommendation #web: Mining recommendations from the web (GS, DMC, CM), pp. 35–42.
SEKE-2008-BahsoonE: An Example on Economics-driven Software Mining (RB, WE), pp. 375–380.
SEKE-2008-DingH #algorithm #named #performance: VP: an Efficient Algorithm for Frequent Itemset Mining (QD, WSH), pp. 381–386.
SEKE-2008-WuSF #clustering #re-engineering: Discovering Meaningful Clusters from Mining the Software Engineering Literature (YW, HPS, LF), pp. 613–618.
SIGIR-2008-HuCBLCY #query #web: Web query translation via web log mining (RH, WC, PB, YL, ZC, QY), pp. 749–750.
SIGIR-2008-ZhouQLBQC #named #overview: SOPING: a Chinese customer review mining system (CZ, GQ, KL, JB, MQ, CC), pp. 741–742.
RE-2008-Castro-HerreraDCM #data mining #elicitation #process #recommendation #requirements #scalability #using: Using Data Mining and Recommender Systems to Facilitate Large-Scale, Open, and Inclusive Requirements Elicitation Processes (CCH, CD, JCH, BM), pp. 165–168.
ASE-2008-LoM: Mining Scenario-Based Triggers and Effects (DL, SM), pp. 109–118.
ASE-2008-ThummalapentaX #detection #framework #named #open source #source code #web: SpotWeb: Detecting Framework Hotspots and Coldspots via Mining Open Source Code on the Web (ST, TX), pp. 327–336.
FSE-2008-GabelS #automation #named: Javert: fully automatic mining of general temporal properties from dynamic traces (MG, ZS), pp. 339–349.
ICSE-2008-GabelS #specification: Symbolic mining of temporal specifications (MG, ZS), pp. 51–60.
ICSE-2008-SankaranarayananIG #induction #library #logic programming #specification #using: Mining library specifications using inductive logic programming (SS, FI, AG), pp. 131–140.
ICSE-2008-SchaferJM #framework: Mining framework usage changes from instantiation code (TS, JJ, MM), pp. 471–480.
SAC-2008-AntonyBHP #approach #biology #interactive #using #validation: Computational approach to biological validation of protein-protein interactions discovered using literature mining (AA, SB, SH, MJP), pp. 1302–1306.
SAC-2008-LaRosaXM #kernel: Frequent pattern mining for kernel trace data (CL, LX, KM), pp. 880–885.
SAC-2008-LiZC #case study: Mining disease-specific molecular association profiles from biomedical literature: a case study (JL, XZ, JYC), pp. 1287–1291.
SAC-2008-MontanaTT #algorithm #data type: Data stream mining for market-neutral algorithmic trading (GM, KT, TT), pp. 966–970.
SAC-2008-WeiSWS #email #forensics #identification: Mining spam email to identify common origins for forensic application (CW, AS, GW, AS), pp. 1433–1437.
SAC-2008-ZengLL #fault tolerance: Mining fault-tolerant frequent patterns efficiently with powerful pruning (JJZ, GL, CCL), pp. 927–931.
CASE-2008-Balasundaram #graph: Cohesive subgroup model for graph-based text mining (BB), pp. 989–994.
CASE-2008-BenedettoDSW #automation #verification: Automatic verification of wireless control in a mining ventilation system (MDDB, AD, ES, EW), pp. 858–863.
CASE-2008-FischionePRST #architecture #automation #communication: Mining ventilation automation: Wireless sensing, communication architecture and advanced services (CF, LP, CR, FS, ST), pp. 851–857.
CASE-2008-WitrantJ #modelling: Air flow modeling in deepwells: Application to mining ventilation (EW, KHJ), pp. 845–850.
DATE-2008-ChengH #invariant #verification: Simulation-Directed Invariant Mining for Software Verification (XC, MSH), pp. 682–687.
HPDC-2008-ShrinivasN #data mining #detection #grid: Issues in applying data mining to grid job failure detection and diagnosis (LS, JFN), pp. 239–240.
HPDC-2008-XiaFJTW #approach #correlation #evaluation #file system #named #novel #optimisation #performance: FARMER: a novel approach to file access correlation mining and evaluation reference model for optimizing peta-scale file system performance (PX, DF, HJ, LT, FW), pp. 185–196.
PDP-2008-GrossF #communication #data mining #feedback #named #ubiquitous: CoDaMine: Communication Data Mining for Feedback and Control in Ubiquitous Environments (TG, MF), pp. 539–546.
PPoPP-2008-TatikondaP #adaptation #approach #architecture #manycore #memory management: An adaptive memory conscious approach for mining frequent trees: implications for multi-core architectures (ST, SP), pp. 263–264.
ICST-2008-ZaidmanRDD #co-evolution #repository: Mining Software Repositories to Study Co-Evolution of Production & Test Code (AZ, BVR, SD, AvD), pp. 220–229.
ICDAR-2007-CeciBPM #approach #data mining #detection #order: A Data Mining Approach to Reading Order Detection (MC, MB, GP, DM), pp. 924–928.
JCDL-2007-MimnoM #library: Mining a digital library for influential authors (DMM, AM), pp. 105–106.
JCDL-2007-SandersonW #library #process: Integrating data and text mining processes for digital library applications (RS, PBW), pp. 73–79.
JCDL-2007-StewartCB #corpus #generative #scalability: A new generation of textual corpora: mining corpora from very large collections (GS, GRC, AB), pp. 356–365.
JCDL-2007-ZhuangELG #quality: Measuring conference quality by mining program committee characteristics (ZZ, EE, DL, CLG), pp. 225–234.
SIGMOD-2007-FaloutsosKS #graph #matrix #scalability #tool support #using: Mining large graphs and streams using matrix and tensor tools (CF, TGK, JS), p. 1174.
SIGMOD-2007-VardeRS #data mining #named #optimisation #process #visual notation: AutoDomainMine: a graphical data mining system for process optimization (ASV, EAR, RDSJ), pp. 1103–1105.
VLDB-2007-GonzalezHLMS #adaptation #approach #network #performance: Adaptive Fastest Path Computation on a Road Network: A Traffic Mining Approach (HG, JH, XL, MM, JPS), pp. 794–805.
VLDB-2007-LiH #approximate #multi: Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data (XL, JH), pp. 447–458.
VLDB-2007-LiL #multi #optimisation: Optimization of Frequent Itemset Mining on Multiple-Core Processor (EL, LL), pp. 1275–1285.
VLDB-2007-WongCHKM #outsourcing #security: Security in Outsourcing of Association Rule Mining (WKW, DWC, EH, BK, NM), pp. 111–122.
CSMR-2007-GrossoPG #approach #database: An approach for mining services in database oriented applications (CDG, MDP, IGRdG), pp. 287–296.
ICPC-2007-KagdiMS #repository #traceability: Mining Software Repositories for Traceability Links (HHK, JIM, BS), pp. 145–154.
ICPC-2007-RoyURD #case study: Evaluating Aspect Mining Techniques: A Case Study (CKR, MGU, BR, TRD), pp. 167–176.
ICSM-2007-AntoniolGMT #evolution: Mining the Lexicon Used by Programmers during Sofware Evolution (GA, YGG, EM, PT), pp. 14–23.
MSR-2007-KagdiCM #source code: Comparing Approaches to Mining Source Code for Call-Usage Patterns (HHK, MLC, JIM), p. 20.
MSR-2007-KieferBT #evolution #ontology #repository: Mining Software Repositories with iSPAROL and a Software Evolution Ontology (CK, AB, JT), p. 10.
MSR-2007-LinsteadRBLB #developer #eclipse #modelling #topic: Mining Eclipse Developer Contributions via Author-Topic Models (EL, PR, SKB, CVL, PB), p. 30.
MSR-2007-Masticola #development #lightweight #repository #using: Lightweight Risk Mitigation for Software Development Projects Using Repository Mining (SPM), p. 13.
MSR-2007-MorisakiMMTM #data analysis #fault: Defect Data Analysis Based on Extended Association Rule Mining (SM, AM, TM, HT, KiM), p. 3.
MSR-2007-Robbes #repository: Mining a Change-Based Software Repository (RR), p. 15.
MSR-2007-WeissgerberPB #data mining #detection #developer #how #visual notation: Visual Data Mining in Software Archives to Detect How Developers Work Together (PW, MP, MB), p. 9.
MSR-2007-YuR #cvs #developer #open source #repository: Mining CVS Repositories to Understand Open-Source Project Developer Roles (LY, SR), p. 8.
MSR-2007-Zimmermann #cvs: Mining Workspace Updates in CVS (TZ), p. 11.
WCRE-2007-RaberL #data mining #debugging #using: Emulated Breakpoint Debugger and Data Mining Using Detours (JR, EL), pp. 271–272.
DiGRA-2007-BraggeS #game studies #profiling #research #tool support #using: Profiling Academic Research on Digital Games Using Text Mining Tools (JB, JS).
HCI-AS-2007-XueL #data mining #distributed #modelling #research #similarity: Research of Distributed Data Mining Association Rules Model Based on Similarity (SX, ZL), pp. 1180–1189.
HCI-MIE-2007-ChevrinC #interactive #multi: Dynamic Association Rules Mining to Improve Intermediation Between User Multi-channel Interactions and Interactive e-Services (VC, OC), pp. 265–274.
HIMI-IIE-2007-KanekoNATT #analysis #generative #using: A Method for Generating Plans for Retail Store Improvements Using Text Mining and Conjoint Analysis (TK, YN, MA, TT, YT), pp. 910–917.
HIMI-MTT-2007-HuangLW #correlation #multi: Mining Attack Correlation Scenarios Based on Multi-agent System (SH, ZL, LW), pp. 632–641.
HIMI-MTT-2007-NishimuraH #approach #case study #data mining #fault #visualisation: The Study of Past Working History Visualization for Supporting Trial and Error Approach in Data Mining (KN, MH), pp. 327–334.
HIMI-MTT-2007-TogawaKY #communication #detection #network #peer-to-peer #using: Peer-to-Peer File Sharing Communication Detection System Using Network Traffic Mining (ST, KK, YY), pp. 769–778.
ICEIS-AIDSS-2007-Aalst #analysis #process #roadmap #verification: Trends in business process analysis — from verification to process mining (WMPvdA), pp. 5–9.
ICEIS-AIDSS-2007-BecksH #analysis #industrial: Trend Analysis Based on Explorative Data and Text Mining: A Decision Support System for the European Home Textile Industry (AB, JH), pp. 253–258.
ICEIS-AIDSS-2007-SokolovaF #architecture #assessment #data mining #multi: A Multi-Agent Architecture for Environmental Impact Assessment: Information Fusion, Data Mining and Decision Making (MVS, AFC), pp. 219–224.
ICEIS-AIDSS-2007-WanzellerB #assessment #data mining #similarity: Similarity Assessment in a CBR Application for Clickstream Data Mining Plans Selection (CW, OB), pp. 137–144.
ICEIS-DISI-2007-Aalst #analysis #process #roadmap #verification: Trends in business process analysis — from verification to process mining (WMPvdA), pp. 5–9.
ICEIS-EIS-2007-Aalst #analysis #process #roadmap #verification: Trends in business process analysis — from verification to process mining (WMPvdA), pp. 5–9.
ICEIS-HCI-2007-Aalst #analysis #process #roadmap #verification: Trends in business process analysis — from verification to process mining (WMPvdA), pp. 5–9.
ICEIS-SAIC-2007-Aalst #analysis #process #roadmap #verification: Trends in business process analysis — from verification to process mining (WMPvdA), pp. 5–9.
CIKM-2007-AngiulliF #performance: Very efficient mining of distance-based outliers (FA, FF), pp. 791–800.
CIKM-2007-DonZGTACSP #visualisation: Discovering interesting usage patterns in text collections: integrating text mining with visualization (AD, EZ, MG, ST, LA, TC, BS, CP), pp. 213–222.
CIKM-2007-ParkR #information retrieval #multi #web: Mining web multi-resolution community-based popularity for information retrieval (LAFP, KR), pp. 545–554.
CIKM-2007-WuHK #web: Mining redundancy in candidate-bearing snippets to improve web question answering (YW, XH, HK), pp. 999–1002.
KDD-2007-ArchakGI #exclamation #power of: Show me the money!: deriving the pricing power of product features by mining consumer reviews (NA, AG, PGI), pp. 56–65.
KDD-2007-CotofreiS #data mining #probability #process: Stochastic processes and temporal data mining (PC, KS), pp. 183–190.
KDD-2007-DouFRFMT #development #framework #ontology: Development of NeuroElectroMagnetic ontologies(NEMO): a framework for mining brainwave ontologies (DD, GAF, JR, RMF, ADM, DMT), pp. 270–279.
KDD-2007-Fayyad #internet #web: From mining the web to inventing the new sciences underlying the internet (UMF), pp. 2–3.
KDD-2007-GaoESCX #consistency #data mining #problem #set: The minimum consistent subset cover problem and its applications in data mining (BJG, ME, JyC, OS, HX), pp. 310–319.
KDD-2007-GiannottiNPP: Trajectory pattern mining (FG, MN, FP, DP), pp. 330–339.
KDD-2007-GuoZXF #data mining #database #learning #multimodal: Enhanced max margin learning on multimodal data mining in a multimedia database (ZG, ZZ, EPX, CF), pp. 340–349.
KDD-2007-JanssensGM #analysis #clustering #hybrid: Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis (FALJ, WG, BDM), pp. 360–369.
KDD-2007-Kleinberg #challenge #network #privacy #process #social: Challenges in mining social network data: processes, privacy, and paradoxes (JMK), pp. 4–5.
KDD-2007-LiLW #equivalence #statistics: Mining statistically important equivalence classes and delta-discriminative emerging patterns (JL, GL, LW), pp. 430–439.
KDD-2007-LoKL #performance #specification: Efficient mining of iterative patterns for software specification discovery (DL, SCK, CL), pp. 460–469.
KDD-2007-NijssenF: Mining optimal decision trees from itemset lattices (SN, ÉF), pp. 530–539.
KDD-2007-PanZZPSPY #modelling #network: Domain-constrained semi-supervised mining of tracking models in sensor networks (RP, JZ, VWZ, JJP, DS, SJP, QY), pp. 1023–1027.
KDD-2007-Parthasarathy #data mining #learning: Data mining at the crossroads: successes, failures and learning from them (SP), pp. 1053–1055.
KDD-2007-SunFPY #graph #named #scalability: GraphScope: parameter-free mining of large time-evolving graphs (JS, CF, SP, PSY), pp. 687–696.
KDD-2007-TongFK #graph #performance #proximity: Fast direction-aware proximity for graph mining (HT, CF, YK), pp. 747–756.
KDD-2007-WangZHS #coordination #correlation #topic: Mining correlated bursty topic patterns from coordinated text streams (XW, CZ, XH, RS), pp. 784–793.
KDD-2007-WongFPW: Mining favorable facets (RCWW, JP, AWCF, KW), pp. 804–813.
KDD-2007-ZhaoDZ #network: Mining complex power networks for blackout prevention (JHZ, ZYD, PZ), pp. 986–994.
KDD-2007-ZhaoMY: Mining templates from search result records of search engines (HZ, WM, CTY), pp. 884–893.
MLDM-2007-AoYHH #data type: Mining Maximal Frequent Itemsets in Data Streams Based on FP-Tree (FA, YY, JH, KH), pp. 479–489.
MLDM-2007-GellerPK: Blog Mining for the Fortune 500 (JG, SP, SK), pp. 379–391.
MLDM-2007-Morzy #predict: Mining Frequent Trajectories of Moving Objects for Location Prediction (MM), pp. 667–680.
MLDM-2007-PalancarTCL #algorithm #distributed #memory management #parallel: Distributed and Shared Memory Algorithm for Parallel Mining of Association Rules (JHP, OFT, JFC, RHL), pp. 349–363.
MLDM-2007-SadoddinG #case study #comparative #data mining #detection #machine learning: A Comparative Study of Unsupervised Machine Learning and Data Mining Techniques for Intrusion Detection (RS, AAG), pp. 404–418.
MLDM-2007-TanN #data mining #privacy #probability #re-engineering: Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining (VYFT, SKN), pp. 76–90.
MLDM-2007-WangLYC #classification #data type #fuzzy #incremental: An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams (TW, ZL, YY, HC), pp. 91–103.
MLDM-2007-WangXC #approach #classification #novel: A Novel Rule Ordering Approach in Classification Association Rule Mining (YJW, QX, FC), pp. 339–348.
RecSys-2007-SandvigMB #collaboration #recommendation #robust: Robustness of collaborative recommendation based on association rule mining (JJS, BM, RDB), pp. 105–112.
SIGIR-2007-DingL: The utility of linguistic rules in opinion mining (XD, BL), pp. 811–812.
PLDI-2007-RamanathanGJ #specification #using: Static specification inference using predicate mining (MKR, AG, SJ), pp. 123–134.
ASE-2007-Kagdi #fine-grained #predict #source code: Improving change prediction with fine-grained source code mining (HHK), pp. 559–562.
ASE-2007-KagdiCM #approach: An approach to mining call-usage patternswith syntactic context (HHK, MLC, JIM), pp. 457–460.
ASE-2007-LinsteadRBLB #concept #modelling #probability #topic: Mining concepts from code with probabilistic topic models (EL, PR, SKB, CVL, PB), pp. 461–464.
ASE-2007-LoMK #execution #specification: Mining modal scenario-based specifications from execution traces of reactive systems (DL, SM, SCK), pp. 465–468.
ESEC-FSE-2007-AcharyaXPX #api #partial order #source code #specification: Mining API patterns as partial orders from source code: from usage scenarios to specifications (MA, TX, JP, JX), pp. 25–34.
ESEC-FSE-2007-ChristodorescuJK #behaviour #specification: Mining specifications of malicious behavior (MC, SJ, CK), pp. 5–14.
ICSE-2007-GanapathyKJJ #concept analysis #legacy #using: Mining Security-Sensitive Operations in Legacy Code Using Concept Analysis (VG, DK, TJ, SJ), pp. 458–467.
SAC-2007-CaldersGM: Mining itemsets in the presence of missing values (TC, BG, MM), pp. 404–408.
SAC-2007-FattaF #data mining #distributed #multi: A customizable multi-agent system for distributed data mining (GDF, GF), pp. 42–47.
SAC-2007-HwangY #ranking: Mining and processing category ranking (SwH, HY), pp. 441–442.
SAC-2007-KimHK #approach #folksonomy: FCA-based approach for mining contextualized folksonomy (HLK, ShH, HGK), pp. 1340–1345.
SAC-2007-Knijf #named: FAT-miner: mining frequent attribute trees (JDK), pp. 417–422.
SAC-2007-LinL #privacy #transaction: Privacy preserving itemset mining through fake transactions (JLL, JYCL), pp. 375–379.
SAC-2007-TengC #community #mobile: Mining communities of acquainted mobile users on call detail records (WGT, MCC), pp. 957–958.
SAC-2007-XiongCL #classification #database #multi #using: Mining multiple private databases using a kNN classifier (LX, SC, LL), pp. 435–440.
CASE-2007-RamachandranEMB #data mining #health: Data Mining in Military Health Systems — Clinical and Administrative Applications (SR, ME, RJM, PCB), pp. 158–163.
DAC-2007-WangBA #correlation #data mining #perspective: Design-Silicon Timing Correlation A Data Mining Perspective (LCW, PB, MSA), pp. 384–389.
DATE-2007-BabighianKV #data mining #interactive #optimisation: Interactive presentation: PowerQuest: trace driven data mining for power optimization (PB, GK, MYV), pp. 1078–1083.
PPoPP-2007-BuehrerPTKS #architecture #towards: Toward terabyte pattern mining: an architecture-conscious solution (GB, SP, ST, TMK, JHS), pp. 2–12.
ISSTA-2007-ShohamYFP #abstraction #specification #using: Static specification mining using automata-based abstractions (SS, EY, SF, MP), pp. 174–184.
DocEng-2006-ZeridaLC: Combining linguistic and structural descriptors for mining biomedical literature (NZ, NL, BC), pp. 62–64.
ECDL-2006-RodriguezLGM #library: The SINAMED and ISIS Projects: Applying Text Mining Techniques to Improve Access to a Medical Digital Library (MdBR, MJML, DG, JMV), pp. 548–551.
HT-2006-KazienkoP #assessment #web: Hyperlink assessment based on web usage mining (PK, MP), pp. 85–88.
JCDL-2006-DownieH #library #music #overview: Review mining for music digital libraries: phase II (JSD, XH), pp. 196–197.
JCDL-2006-PlaisantRYAKSCL #interface #visual notation: Exploring erotics in Emily Dickinson’s correspondence with text mining and visual interfaces (CP, JR, BY, LA, MGK, MNS, TC, GL), pp. 141–150.
SIGMOD-2006-BorgwardtBK #graph #named #visual notation: VGM: visual graph mining (KMB, SB, HPK), pp. 733–735.
VLDB-2006-JiTT #3d #dataset: Mining Frequent Closed Cubes in 3D Datasets (LJ, KLT, AKHT), pp. 811–822.
VLDB-2006-Keogh #database #scalability: A Decade of Progress in Indexing and Mining Large Time Series Databases (EJK), p. 1268.
VLDB-2006-LeglerLR #data mining: Data Mining with the SAP Netweaver BI Accelerator (TL, WL, AR), pp. 1059–1068.
VLDB-2006-RodriguesTTFL #graph #interactive #named #scalability #visualisation: GMine: A System for Scalable, Interactive Graph Visualization and Mining (JFRJ, HT, AJMT, CF, JL), pp. 1195–1198.
VLDB-2006-SteinleAGL #dependence #generative #novel: Mapping Moving Landscapes by Mining Mountains of Logs: Novel Techniques for Dependency Model Generation (MS, KA, SG, CL), pp. 1093–1102.
ITiCSE-2006-MarkovR #data mining: An introduction to the WEKA data mining system (ZM, IR), pp. 367–368.
ICPC-2006-SafyallahS #dynamic analysis #execution #using: Dynamic Analysis of Software Systems using Execution Pattern Mining (HS, KS), pp. 84–88.
ICPC-2006-ZaidmanBD #comprehension #how #metric: How Webmining and Coupling Metrics Improve Early Program Comprehension (AZ, BDB, SD), pp. 74–78.
ICSM-2006-Hassan #developer #repository: Mining Software Repositories to Assist Developers and Support Managers (AEH), pp. 339–342.
MSR-2006-BirdGDGS #email #network #social: Mining email social networks (CB, AG, PTD, MG, AS), pp. 137–143.
MSR-2006-BirdGDGS06a #email #network #social: Mining email social networks in Postgres (CB, AG, PTD, MG, AS), pp. 185–186.
MSR-2006-BreuZL #eclipse: Mining eclipse for cross-cutting concerns (SB, TZ, CL), pp. 94–97.
MSR-2006-HammoudaK #repository: Concern based mining of heterogeneous software repositories (IH, KK), pp. 80–86.
MSR-2006-KagdiYM #sequence #version control: Mining sequences of changed-files from version histories (HHK, SY, JIM), pp. 47–53.
MSR-2006-KimZKHMGPWZ #named #repository: TA-RE: an exchange language for mining software repositories (SK, TZ, MK, AEH, AM, TG, MP, EJWJ, AZ), pp. 22–25.
MSR-2006-RoblesGMA #evolution #scalability: Mining large software compilations over time: another perspective of software evolution (GR, JMGB, MM, JJA), pp. 3–9.
MSR-2006-VoineaT06a #repository: Mining software repositories with CVSgrab (LV, ACT), pp. 167–168.
MSR-2006-WeissgerberDG #refactoring: Mining refactorings in ARGOUML (PW, SD, CG), pp. 175–176.
MSR-2006-XieP #api #named #open source #repository: MAPO: mining API usages from open source repositories (TX, JP), pp. 54–57.
MSR-2006-YangR #architecture #evolution: Scenarios for mining the software architecture evolution (YY, CR), pp. 10–13.
MSR-2006-ZimmermannBLL: Mining additions of method calls in ArgoUML (TZ, SB, CL, VBL), pp. 169–170.
MSR-2006-ZimmermannKZW: Mining version archives for co-changed lines (TZ, SK, AZ, EJWJ), pp. 72–75.
SCAM-2006-FulopGF #c++ #design pattern #tool support: Evaluating C++ Design Pattern Miner Tools (LJF, TG, RF), pp. 127–138.
WCRE-2006-Krinke #control flow #graph: Mining Control Flow Graphs for Crosscutting Concerns (JK), pp. 334–342.
WCRE-2006-MarinMD #framework: A common framework for aspect mining based on crosscutting concern sorts (MM, LM, AvD), pp. 29–38.
WCRE-2006-MarinMD06a #named #tool support: FINT: Tool Support for Aspect Mining (MM, LM, AvD), pp. 299–300.
ICEIS-AIDSS-2006-BoudjeloudP #data mining #interactive: Semi Interactive Method for Data Mining (LB, FP), pp. 3–10.
ICEIS-AIDSS-2006-GollerHS #algorithm #data mining: Beneficial Sequential Combination of Data Mining Algorithms (MG, MH, MS), pp. 135–143.
ICEIS-AIDSS-2006-PintoGS #data mining #database #paradigm: Data Mining as a New Paradigm for Business Intelligence in Database Marketing Projects (FMP, PG, MFS), pp. 144–149.
ICEIS-HCI-2006-BadjioP #analysis #data mining #process #visual notation: Context of Use Analysis — Activity Checklist for Visual Data Mining (EPFB, FP), pp. 45–50.
ICEIS-ISAS-2006-DaoHHRV #abstraction #modelling #tool support #towards #uml: Towards Practical Tools for Mining Abstractions in UML Models (MD, MH, MRH, CR, PV), pp. 276–283.
CIKM-2006-GonzalezHL #set #workflow: Mining compressed commodity workflows from massive RFID data sets (HG, JH, XL), pp. 162–171.
CIKM-2006-HuangTOC #on the: On progressive sequential pattern mining (JWH, CYT, JCO, MSC), pp. 850–851.
CIKM-2006-HuZZ #array #clustering #identification #integration: Integration of cluster ensemble and EM based text mining for microarray gene cluster identification and annotation (XH, XZ, XZ), pp. 824–825.
CIKM-2006-KapoorPTT #database #distributed #privacy: Privacy preserving sequential pattern mining in distributed databases (VK, PP, FT, MT), pp. 758–767.
CIKM-2006-KimC #concept #named #similarity #taxonomy: CP/CV: concept similarity mining without frequency information from domain describing taxonomies (JWK, KSC), pp. 483–492.
CIKM-2006-KunkleZC #performance: Efficient mining of max frequent patterns in a generalized environment (DK, DZ, GC), pp. 810–811.
CIKM-2006-QamraTC #clustering #using: Mining blog stories using community-based and temporal clustering (AQ, BLT, EYC), pp. 58–67.
CIKM-2006-TatikondaPK #algorithm: TRIPS and TIDES: new algorithms for tree mining (ST, SP, TMK), pp. 455–464.
CIKM-2006-ZhangW #array: Mining coherent patterns from heterogeneous microarray data (XZ, WW), pp. 838–839.
CIKM-2006-ZhuangJZ #overview #summary: Movie review mining and summarization (LZ, FJ, XZ), pp. 43–50.
ICML-2006-TsudaK #clustering #graph: Clustering graphs by weighted substructure mining (KT, TK), pp. 953–960.
ICPR-v1-2006-BethelHG: Mining for Implications in Medical Data (CLB, LOH, DBG), pp. 1212–1215.
ICPR-v1-2006-CantoniLL #challenge #data mining #distributed #network: Challenges for Data Mining in Distributed Sensor Networks (VC, LL, PL), pp. 1000–1007.
ICPR-v2-2006-YuW06b #nondeterminism: Mining Uncertain Data in Low-dimensional Subspace (ZY, HSW), pp. 748–751.
ICPR-v3-2006-NockLS #incremental #statistics: Statistical Borders for Incremental Mining (RN, PAL, JES), pp. 212–215.
ICPR-v3-2006-VilchesEVT #data mining #recognition: Data Mining Applied to Acoustic Bird Species Recognition (EV, IAE, EEV, CET), pp. 400–403.
ICPR-v3-2006-ZhouK #detection #multi #video: Unusual Event Detection via Multi-camera Video Mining (HZ, DK), pp. 1161–1166.
KDD-2006-AggarwalPZ #data mining #on the #privacy: On privacy preservation against adversarial data mining (CCA, JP, BZ), pp. 510–516.
KDD-2006-AgichteinZ #behaviour #identification #web: Identifying “best bet” web search results by mining past user behavior (EA, ZZ), pp. 902–908.
KDD-2006-BuehrerPG: Out-of-core frequent pattern mining on a commodity PC (GB, SP, AG), pp. 86–95.
KDD-2006-CaldersGJ #set: Mining rank-correlated sets of numerical attributes (TC, BG, SJ), pp. 96–105.
KDD-2006-CaruanaEMRSFHK #predict: Mining citizen science data to predict orevalence of wild bird species (RC, MFE, AM, MR, DS, DF, WMH, SK), pp. 909–915.
KDD-2006-Cavaretta #challenge #data mining: Data mining challenges in the automotive domain (MC), p. 836.
KDD-2006-FormanKS: Pragmatic text mining: minimizing human effort to quantify many issues in call logs (GF, EK, JS), pp. 852–861.
KDD-2006-GionisMMT #data mining: Assessing data mining results via swap randomization (AG, HM, TM, PT), pp. 167–176.
KDD-2006-GuoV #multi #relational #validation: Mining relational data through correlation-based multiple view validation (HG, HLV), pp. 567–573.
KDD-2006-HashimotoAUKM #order #performance #probability: A new efficient probabilistic model for mining labeled ordered trees (KH, KFAK, NU, MK, HM), pp. 177–186.
KDD-2006-HettichP #lessons learnt: Mining for proposal reviewers: lessons learned at the national science foundation (SH, MJP), pp. 862–871.
KDD-2006-HorvathRW #graph: Frequent subgraph mining in outerplanar graphs (TH, JR, SW), pp. 197–206.
KDD-2006-JiangG #data type #named: CFI-Stream: mining closed frequent itemsets in data streams (NJ, LG), pp. 592–597.
KDD-2006-KeCN #approach #correlation #using: Mining quantitative correlated patterns using an information-theoretic approach (YK, JC, WN), pp. 227–236.
KDD-2006-LingSBM #development: Maximum profit mining and its application in software development (CXL, VSS, TFWB, NHM), pp. 929–934.
KDD-2006-LoekitoB #diagrams #performance #using: Fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams (EL, JB), pp. 307–316.
KDD-2006-ManiyarN #algorithm #data mining #using #visual notation #visualisation: Visual data mining using principled projection algorithms and information visualization techniques (DMM, ITN), pp. 643–648.
KDD-2006-McCallum #data mining #information management: Information extraction, data mining and joint inference (AM), p. 835.
KDD-2006-MeiZ: A mixture model for contextual text mining (QM, CZ), pp. 649–655.
KDD-2006-MierswaWKSE #agile #data mining #named #prototype: YALE: rapid prototyping for complex data mining tasks (IM, MW, RK, MS, TE), pp. 935–940.
KDD-2006-Morchen #algorithm: Algorithms for time series knowledge mining (FM), pp. 668–673.
KDD-2006-PalatinLSW #grid: Mining for misconfigured machines in grid systems (NP, AL, AS, RW), pp. 687–692.
KDD-2006-PanGBXTF #automation #image: Automatic mining of fruit fly embryo images (JYP, AGRB, EPX, AJMT, CF), pp. 693–698.
KDD-2006-Piatetsky-ShapiroGDFGZ #challenge #data mining #question: Is there a grand challenge or X-prize for data mining? (GPS, RG, CD, RF, LG, MJZ), pp. 954–956.
KDD-2006-TanSZ: Mining long-term search history to improve search accuracy (BT, XS, CZ), pp. 718–723.
KDD-2006-TaoXZ #database #metric #scalability: Mining distance-based outliers from large databases in any metric space (YT, XX, SZ), pp. 394–403.
KDD-2006-WangYPYY #concept #data type: Suppressing model overfitting in mining concept-drifting data streams (HW, JY, JP, PSY, JXY), pp. 736–741.
KDD-2006-ZhangHL: Mining progressive confident rules (MZ, WH, MLL), pp. 803–808.
KDD-2006-ZhaoLBX #data mining #identification: Opportunity map: identifying causes of failure — a deployed data mining system (KZ, BL, JB, WX), pp. 892–901.
KDD-2006-ZhaoZR #framework #named: BLOSOM: a framework for mining arbitrary boolean expressions (LZ, MJZ, NR), pp. 827–832.
SEKE-2006-BogornyEA #framework #named #preprocessor: GEOARM: an Interoperable Framework to Improve Geographic Data Preprocessing and Spatial Association Rule Mining (VB, PME, LOA), pp. 79–84.
SEKE-2006-CazellaA #architecture #data mining #multi #recommendation #research: An architecture based on multi-agent system and data mining for recommending research papers and researchers (SCC, LOCA), pp. 67–72.
SEKE-2006-GaaloulG #analysis #statistics #workflow: A Workflow Mining Tool based on Logs Statistical Analysis (WG, CG), pp. 595–600.
SEKE-2006-HungL #data mining #performance #using: Using Data Mining Schemes for Improvement on System Performance in Virtual Environments (SSH, DSML), pp. 61–66.
SEKE-2006-SartipiS #analysis #concept #evaluation #execution: Application of Execution Pattern Mining and Concept Lattice Analysis on Software Structure Evaluation (KS, HS), pp. 302–308.
SIGIR-2006-SunOC #dependence #query #retrieval: Mining dependency relations for query expansion in passage retrieval (RS, CHO, TSC), pp. 382–389.
OOPSLA-2006-SahavechaphanC #named: XSnippet: mining For sample code (NS, KTC), pp. 413–430.
LOPSTR-2006-AbdennadherOST #automation #named: ARM: Automatic Rule Miner (SA, AO, NS, AT), pp. 17–25.
ASE-2006-BreuZ #aspect-oriented #version control: Mining Aspects from Version History (SB, TZ), pp. 221–230.
FSE-2006-LoK #named #robust #scalability #specification #towards: SMArTIC: towards building an accurate, robust and scalable specification miner (DL, SCK), pp. 265–275.
ICSE-2006-NagappanBZ #component #metric #predict: Mining metrics to predict component failures (NN, TB, AZ), pp. 452–461.
ICSE-2006-YangEBBD #api #named: Perracotta: mining temporal API rules from imperfect traces (JY, DE, DB, TB, MD), pp. 282–291.
SAC-2006-AbidinP #classification #data mining #named #nearest neighbour #performance #scalability: SMART-TV: a fast and scalable nearest neighbor based classifier for data mining (TA, WP), pp. 536–540.
SAC-2006-FengQWZ #query #xml: Exploit sequencing to accelerate hot XML query pattern mining (JF, QQ, JW, LZ), pp. 517–524.
SAC-2006-GamaP #data mining #data type: Discretization from data streams: applications to histograms and data mining (JG, CP), pp. 662–667.
SAC-2006-GiannottiNPP #sequence: Mining sequences with temporal annotations (FG, MN, DP, FP), pp. 593–597.
SAC-2006-GuoW #data mining #on the #privacy #using: On the use of spectral filtering for privacy preserving data mining (SG, XW), pp. 622–626.
SAC-2006-MaC #algorithm #array #data mining #network #novel: A novel data mining algorithm for reconstructing gene regulatory networks from microarray data (PCHM, KCCC), pp. 202–203.
SAC-2006-TsengCL #e-commerce #navigation #personalisation #predict: Mining and prediction of temporal navigation patterns for personalized services in e-commerce (VST, JCC, KWL), pp. 867–871.
SAC-2006-WuH #interactive #network: Mining and analyzing the topological structure of protein-protein interaction networks (DDW, XH), pp. 185–189.
SAC-2006-ZhouHCPB: Approaches to text mining for clinical medical records (XZ, HH, IC, AP, ADB), pp. 235–239.
DAC-2006-WuH #bound #constraints #equivalence: Mining global constraints for improving bounded sequential equivalence checking (WW, MSH), pp. 743–748.
HPCA-2006-JaleelMJ #case study #data mining #parallel #performance: Last level cache (LLC) performance of data mining workloads on a CMP — a case study of parallel bioinformatics workloads (AJ, MM, BLJ), pp. 88–98.
HPDC-2006-CieslakTC #data mining #distributed: Troubleshooting Distributed Systems via Data Mining (DAC, DT, NVC), pp. 309–312.
PODS-2005-CormodeM #multi #performance: Space efficient mining of multigraph streams (GC, SM), pp. 271–282.
PODS-2005-LiLWFT #data mining #perspective: Relative risk and odds ratio: a data mining perspective (HL, JL, LW, MF, YPT), pp. 368–377.
SIGMOD-2005-CongTTX: Mining Top-k Covering Rule Groups for Gene Expression Data (GC, KLT, AKHT, XX), pp. 670–681.
SIGMOD-2005-GovindarajuRM #approximate #performance #using: Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors (NKG, NR, DM), pp. 611–622.
SIGMOD-2005-LuoTWZ #data type #sql: A native extension of SQL for mining data streams (CL, HT, HW, CZ), pp. 873–875.
SIGMOD-2005-SakuraiPF #correlation #named: BRAID: Stream Mining through Group Lag Correlations (YS, SP, CF), pp. 599–610.
SIGMOD-2005-ZhangKCY #sequence: Mining Periodic Patterns with Gap Requirement from Sequences (MZ, BK, DWLC, KYY), pp. 623–633.
SIGMOD-2005-ZhaoZ #3d #algorithm #array #clustering #effectiveness #named: TriCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data (LZ, MJZ), pp. 694–705.
VLDB-2005-ChiWY #data type #named: Loadstar: Load Shedding in Data Stream Mining (YC, HW, PSY), pp. 1303–1305.
VLDB-2005-CormodeMR #data type: Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling (GC, SM, IR), pp. 25–36.
VLDB-2005-GhotingBPKNCD: Cache-conscious Frequent Pattern Mining on a Modern Processor (AG, GB, SP, DK, ADN, YKC, PD), pp. 577–588.
VLDB-2005-XinHYC #set: Mining Compressed Frequent-Pattern Sets (DX, JH, XY, HC), pp. 709–720.
ITiCSE-2005-Roiger #data mining #education: Teaching an introductory course in data mining (RJR), p. 415.
CSMR-2005-ZaidmanCDP #comprehension #execution #process: Applying Webmining Techniques to Execution Traces to Support the Program Comprehension Process (AZ, TC, SD, JP), pp. 134–142.
ICSM-2005-FerencBFL #design pattern #machine learning: Design Pattern Mining Enhanced by Machine Learning (RF, ÁB, LJF, JL), pp. 295–304.
IWPC-2005-CeccatoMMMTT #comparison: A Qualitative Comparison of Three Aspect Mining Techniques (MC, MM, KM, LM, PT, TT), pp. 13–22.
MSR-2005-AntoniolRV #linear #predict #repository: Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories (GA, VFR, GV), pp. 61–65.
MSR-2005-FischerORG #evolution #product line: Mining evolution data of a product family (MF, JO, JR, HCG), pp. 36–40.
MSR-2005-GermanCS #comprehension #development #framework #tool support: A framework for describing and understanding mining tools in software development (DMG, DC, MADS), pp. 31–35.
MSR-2005-HayesDS #feedback #how #re-engineering: Text mining for software engineering: how analyst feedback impacts final results (JHH, AD, SKS), pp. 56–60.
MSR-2005-HuangL #learning #process #verification #version control: Mining version histories to verify the learning process of Legitimate Peripheral Participants (SKH, KmL), pp. 21–25.
MSR-2005-KagdiCM #repository #source code #taxonomy #towards: Towards a taxonomy of approaches for mining of source code repositories (HHK, MLC, JIM), pp. 26–30.
MSR-2005-MierleLRW #cvs #performance #repository #student: Mining student CVS repositories for performance indicators (KM, KL, STR, GW), pp. 105–109.
MSR-2005-OhbaG #concept #identifier #keyword #scalability #towards: Toward mining “concept keywords” from identifiers in large software projects (MO, KG), pp. 11–15.
MSR-2005-SpaccoSHP #automation #programming #repository #testing: Software repository mining with Marmoset: an automated programming project snapshot and testing system (JS, JS, DH, WP), pp. 46–50.
MSR-2005-VanHilstGL #process #repository: Repository mining and Six Sigma for process improvement (MVH, PKG, CL), pp. 101–104.
MSR-2005-YingWA #eclipse #repository #source code: Source code that talks: an exploration of Eclipse task comments and their implication to repository mining (ATTY, JLW, SA), pp. 91–95.
SCAM-2005-Breu: Extending Dynamic Aspect Mining with Static Information (SB), pp. 57–65.
TLCA-2005-MatwinFHC #data mining #formal method #privacy #using: Privacy in Data Mining Using Formal Methods (SM, APF, ITH, VC), pp. 278–292.
SOFTVIS-2005-BurchDW #data mining #visual notation: Visual data mining in software archives (MB, SD, PW), pp. 37–46.
ICEIS-v2-2005-DoP #dataset #scalability #visualisation: Mining Very Large Datasets with SVM and Visualization (TND, FP), pp. 127–141.
ICEIS-v2-2005-KianmehrZNOA #approach #data mining #network: Combining Neural Network and Support Vector Machine into Integrated Approach for Biodata Mining (KK, HZ, KN, TÖ, RA), pp. 182–187.
ICEIS-v2-2005-KumarKDB #clustering #using #web: Web Usage Mining Using Rough Agglomerative Clustering (PK, PRK, SKD, RSB), pp. 315–320.
ICEIS-v2-2005-SantosPS #clustering #data mining #framework #modelling: A Cluster Framework for Data Mining Models — An Application to Intensive Medicine (MFS, JP, ÁMS), pp. 163–168.
ICEIS-v3-2005-EspositoMORS #data mining #detection #novel #realtime: Real Time Detection of Novel Attacks by Means of Data Mining Techniques (ME, CM, FO, SPR, CS), pp. 120–127.
ICEIS-v5-2005-BadjioP #data mining #metric #quality #tool support #visual notation: Visual Data Mining Tools: Quality Metrics Definition and Application (EPFB, FP), pp. 98–103.
CIKM-2005-Ahonen-Myka #sequence #set #word: Mining all maximal frequent word sequences in a set of sentences (HAM), pp. 255–256.
CIKM-2005-CarinoJLWY #machine learning #web: Mining officially unrecognized side effects of drugs by combining web search and machine learning (CC, YJ, BL, PMW, CTY), pp. 365–372.
CIKM-2005-HuangLH #approach #distributed #permutation: A new permutation approach for distributed association rule mining (YH, ZL, HH), pp. 351–352.
CIKM-2005-HuYSZS #semantics: Mining undiscovered public knowledge from complementary and non-interactive biomedical literature through semantic pruning (XH, IY, MS, YZ, IYS), pp. 249–250.
CIKM-2005-KumamotoT #people #web: Web opinion poll: extracting people’s view by impression mining from the web (TK, KT), pp. 265–266.
CIKM-2005-LiL #community: Mining community structure of named entities from free text (XL, BL), pp. 275–276.
CIKM-2005-LiuZ #relational #xml: Relational computation for mining association rules from XML data (HCL, JZ), pp. 253–254.
CIKM-2005-WangHL #database #framework: A framework for mining topological patterns in spatio-temporal databases (JW, WH, MLL), pp. 429–436.
CIKM-2005-ZhaoBG #query #xml: Mining conserved XML query paths for dynamic-conscious caching (QZ, SSB, LG), pp. 219–220.
ECIR-2005-Baeza-Yates #query #web: Applications of Web Query Mining (RABY), pp. 7–22.
KDD-2005-BesemannD #integration #markov: Integration of profile hidden Markov model output into association rule mining (CB, AD), pp. 538–543.
KDD-2005-ChenW #web: Web mining from competitors’ websites (XC, YfBW), pp. 550–555.
KDD-2005-CongHP #parallel: Parallel mining of closed sequential patterns (SC, JH, DAP), pp. 562–567.
KDD-2005-FanLH #image #learning #semantics #statistics: Mining images on semantics via statistical learning (JF, HL, MSH), pp. 22–31.
KDD-2005-Fulgoni #internet: Mining the internet: the eighth wonder of the world (GF), p. 2.
KDD-2005-GoethalsHB #graph #query: Mining tree queries in a graph (BG, EH, JVdB), pp. 61–69.
KDD-2005-JinSA #information management #optimisation: Simultaneous optimization of complex mining tasks with a knowledgeable cache (RJ, KS, GA), pp. 600–605.
KDD-2005-KalosR #data mining #industrial: Data mining in the chemical industry (ANK, TR), pp. 763–769.
KDD-2005-KoppelSZ #fault: Determining an author’s native language by mining a text for errors (MK, JS, KZ), pp. 624–628.
KDD-2005-LiFHCJMWSK: Mining risk patterns in medical data (JL, AWCF, HH, JC, HJ, DM, GJW, RS, CK), pp. 770–775.
KDD-2005-LiLMP #framework: An integrated framework on mining logs files for computing system management (TL, FL, SM, WP), pp. 776–781.
KDD-2005-MeiZ: Discovering evolutionary theme patterns from text: an exploration of temporal text mining (QM, CZ), pp. 198–207.
KDD-2005-MorinagaAISA #dependence #semantics: Key semantics extraction by dependency tree mining (SM, HA, TI, YS, SA), pp. 666–671.
KDD-2005-NasraouiCR #metric #retrieval #similarity #using #web: Using retrieval measures to assess similarity in mining dynamic web clickstreams (ON, CC, CR), pp. 439–448.
KDD-2005-PeiJZ #clique #on the: On mining cross-graph quasi-cliques (JP, DJ, AZ), pp. 228–238.
KDD-2005-Petrushin #multi #self #using #video: Mining rare and frequent events in multi-camera surveillance video using self-organizing maps (VAP), pp. 794–800.
KDD-2005-Scholz: Sampling-based sequential subgroup mining (MS), pp. 265–274.
KDD-2005-SilvaZS #probability #workflow: Probabilistic workflow mining (RBdAeS, JZ, JGS), pp. 275–284.
KDD-2005-TaoZ #corpus #integration: Mining comparable bilingual text corpora for cross-language information integration (TT, CZ), pp. 691–696.
KDD-2005-YamanishiM #monitoring #network: Dynamic syslog mining for network failure monitoring (KY, YM), pp. 499–508.
KDD-2005-YangPM #framework: A generalized framework for mining spatio-temporal patterns in scientific data (HY, SP, SM), pp. 716–721.
KDD-2005-YanZH #constraints #graph #relational: Mining closed relational graphs with connectivity constraints (XY, XJZ, JH), pp. 324–333.
KDD-2005-ZakiPAS #algorithm #category theory #clustering #dataset #effectiveness #named: CLICKS: an effective algorithm for mining subspace clusters in categorical datasets (MJZ, MP, IA, TS), pp. 736–742.
KDD-2005-ZakiR #reasoning #set #using: Reasoning about sets using redescription mining (MJZ, NR), pp. 364–373.
MLDM-2005-AdegoriteBKS #approach: An Approach to Mining Picture Objects Based on Textual Cues (AIA, OAB, MSK, KBS), pp. 466–475.
MLDM-2005-BichindaritzA #concept: Concept Mining for Indexing Medical Literature (IB, SA), pp. 682–691.
MLDM-2005-GillamA: Pattern Mining Across Domain-Specific Text Collections (LG, KA), pp. 570–579.
MLDM-2005-KarrasMGO: Improved MRI Mining by Integrating Support Vector Machine Priors in the Bayesian Restoration (DAK, BGM, DGD, DvO), pp. 325–333.
MLDM-2005-KuhlmannVLT #data mining #simulation: Data Mining on Crash Simulation Data (AK, RMV, CL, CAT), pp. 558–569.
MLDM-2005-MottlKSM #data mining #kernel #multi: Principles of Multi-kernel Data Mining (VM, OK, OS, IBM), pp. 52–61.
MLDM-2005-PrayR: Mining Expressive Temporal Associations from Complex Data (KAP, CR), pp. 384–394.
MLDM-2005-SharmaVTV #approach #database #multi #novel: A Novel Approach of Multilevel Positive and Negative Association Rule Mining for Spatial Databases (LKS, OPV, UST, RV), pp. 620–629.
MLDM-2005-VermaVV #approach #using: Temporal Approach to Association Rule Mining Using T-Tree and P-Tree (KV, OPV, RV), pp. 651–659.
MLDM-2005-XiaWZL #data mining #modelling #random: Mixture Random Effect Model Based Meta-analysis for Medical Data Mining (YX, SW, CZ, SL), pp. 630–640.
MLDM-2005-YeWWCHT #approach: An Integrated Approach for Mining Meta-rules (FY, JW, SW, HC, TH, LT), pp. 549–557.
SEKE-2005-BogornyEA #data mining #framework: A Reuse-based Spatial Data Preparation Framework for Data Mining (VB, PME, LOA), pp. 649–652.
SEKE-2005-ChanS #data mining #rule-based: From Data to Knowledge: an Integrated Rule-Based Data Mining System (CCC, ZS), pp. 508–513.
SEKE-2005-HuangLF #automation #email #query: A Chinese Text Mining Application: An Automatic Answer Reply to Customers’ E-mail Queries Model (JYH, HML, CLF), pp. 504–507.
SEKE-2005-LoYT #algorithm #predict: Weighted Binary Sequential Mining Algorithm with Application to the Next-Day Appearance Prediction (SL, JY, FCT), pp. 783–782.
SIGIR-2005-MagalhaesR #concept #incremental #information management #multi: Mining multimedia salient concepts for incremental information extraction (JM, SMR), pp. 641–642.
SIGIR-2005-SehgalS #named: Manjal: a text mining system for MEDLINE (AKS, PS), p. 680.
SIGIR-2005-SherfeseeO #framework #platform #research #web: A web mining research platform (DS, NO), p. 682.
SIGIR-2005-ZhangHV #query #web: Mining translations of OOV terms from the web through cross-lingual query expansion (YZ, FH, SV), pp. 669–670.
PLDI-2005-MandelinXBK #api: Jungloid mining: helping to navigate the API jungle (DM, LX, RB, DK), pp. 48–61.
ASE-2005-DenmatDR #data mining #execution: Data mining and cross-checking of execution traces: a re-interpretation of Jones, Harrold and Stasko test information (TD, MD, OR), pp. 396–399.
ASE-2005-ShepherdPPC #analysis #automation #framework #named: Timna: a framework for automatically combining aspect mining analyses (DCS, JP, LLP, MCC), pp. 184–193.
ESEC-FSE-2005-LivshitsZ #fault #named: DynaMine: finding common error patterns by mining software revision histories (VBL, TZ), pp. 296–305.
SAC-2005-AgyemangBA #n-gram #using #web: Mining web content outliers using structure oriented weighting techniques and N-grams (MA, KB, RA), pp. 482–487.
SAC-2005-Casale #analysis #network #performance #web: Combining queueing networks and web usage mining techniques for web performance analysis (GC), pp. 1699–1703.
SAC-2005-Morimoto #transitive: Optimized transitive association rule: mining significant stopover between events (YM), pp. 543–544.
SAC-2005-RahalRPNPRV #biology #incremental #interactive: Incremental interactive mining of constrained association rules from biological annotation data with nominal features (IR, DR, AP, HN, WP, RR, WVG), pp. 123–127.
SAC-2005-ShangS #database #relational: Depth-first frequent itemset mining in relational databases (XS, KUS), pp. 1112–1117.
SAC-2005-SilvestriO #approximate #distributed: Distributed approximate mining of frequent patterns (CS, SO), pp. 529–536.
SAC-2005-XuMY #concept #database #information management #scalability: Mining concept associations for knowledge discovery in large textual databases (XX, MM, NY), pp. 549–550.
PPoPP-2005-CongHHP #data mining #framework #parallel: A sampling-based framework for parallel data mining (SC, JH, JH, DAP), pp. 255–265.
TACAS-2005-WeimerN #detection #fault #specification: Mining Temporal Specifications for Error Detection (WW, GCN), pp. 461–476.
ICLP-2005-Saidi #bound #process #using: Using CLP to Characterise Linguistic Lattice Boundaries in a Text Mining Process (ASS), pp. 418–420.
WICSA-2004-ZhuBJ #architecture #evaluation: Mining Patterns to Support Software Architecture Evaluation (LZ, MAB, DRJ), pp. 25–36.
JCDL-2004-LamCH #online: Mining events and new name translations from online daily news (WL, PSC, RH), pp. 287–295.
SIGMOD-2004-AndritsosMT #database #scalability #set #tool support: Information-Theoretic Tools for Mining Database Structure from Large Data Sets (PA, RJM, PT), pp. 731–742.
SIGMOD-2004-CaiCPHWA #data type #named: MAIDS: Mining Alarming Incidents from Data Streams (YDC, DC, GP, JH, MW, LA), pp. 919–920.
SIGMOD-2004-Faloutsos: Indexing and Mining Streams (CF), p. 969.
VLDB-2004-AgrawalS #data mining #question: Whither Data Mining? (RA, RS), p. 9.
VLDB-2004-JiangPZ #interactive #named: GPX: Interactive Mining of Gene Expression Data (DJ, JP, AZ), pp. 1249–1252.
VLDB-2004-LinKLLN #database #monitoring #named #visual notation: VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Databases (JL, EJK, SL, JPL, DMN), pp. 1269–1272.
VLDB-2004-XuCOTH #analysis #semantics: Semantic Mining and Analysis of Gene Expression Data (XX, GC, BCO, KLT, AKHT), pp. 1261–1264.
VLDB-2004-YuCLZ #data type #transaction: False Positive or False Negative: Mining Frequent Itemsets from High Speed Transactional Data Streams (JXY, ZC, HL, AZ), pp. 204–215.
IWPC-2004-KanellopoulosT #c++ #clustering #comprehension #data mining #source code: Data Mining Source Code to Facilitate Program Comprehension: Experiments on Clustering Data Retrieved from C++ Programs (YK, CT), pp. 214–225.
SCAM-2004-TourweM #concept analysis #using: Mining Aspectual Views using Formal Concept Analysis (TT, KM), pp. 97–106.
WCRE-2004-TonellaC #concept analysis #execution: Aspect Mining through the Formal Concept Analysis of Execution Traces (PT, MC), pp. 112–121.
ICEIS-v1-2004-BouchouCAJL #named #xml: XRM: An XML-Based Language for Rule Mining Systems (BB, AC, MHFA, TYJ, DL), pp. 441–446.
ICEIS-v1-2004-El-SonbatyK #algorithm #incremental #performance: New Fast Algorithm for Incremental Mining of Association Rules (YES, RK), pp. 275–281.
ICEIS-v2-2004-BangDHD #concept #data mining #effectiveness #framework #knowledge base #segmentation: Data Mining of CRM Knowledge Bases for Effective Market Segmentation: A Conceptual Framework (JB, ND, LH, RRD), pp. 335–342.
ICEIS-v2-2004-DangerRB #approach #named: Objectminer: A New Approach for Mining Complex Objects (RD, JRS, RBL), pp. 42–47.
ICEIS-v2-2004-DoP #data mining #tool support #towards #visualisation: Towards High Dimensional Data Mining with Boosting of PSVM and Visualization Tools (TND, FP), pp. 36–41.
ICEIS-v2-2004-DykC #education #process #statistics: Warehousing and Mining of Higher Education Data by Means of Statistical Process Control (LVD, PC), pp. 110–115.
ICEIS-v2-2004-HamzaY #constraints #regular expression #using: Mining Sequential Patterns with Regular Expression Constraints Using Sequential Pattern Tree (MH, KM, MY), pp. 116–121.
ICEIS-v2-2004-HuysmansMVB #web: Web Usage Mining with Time Constrained Association Rules (JH, CM, JV, BB), pp. 343–348.
ICEIS-v2-2004-KooptiwootS #set #using: Mining the Relationships in the Form of the Predisposing Factors and Coincident Factors Among Numerical Dynamic Attributes in Time Series Data Set by Using the Combination of Some Existing Techniques (SK, MAS), pp. 327–334.
ICEIS-v2-2004-KooptiwootS04a #idea #set #using: Mining the Relationships in the Form of Predisposing Factor and Coincident Factor in Time Series Data Set by Using the Combination of some Existing Ideas with a new Idea from the Fact in the Chemical Reaction (SK, MAS), pp. 531–534.
ICEIS-v2-2004-KuusikLV #clique #data mining: Data Mining: Pattern Mining as a Clique Extracting Task (RK, GL, LV), pp. 519–522.
ICEIS-v2-2004-MataRR #case study #data mining #development: Applying Data Mining to Software Development Projects: A Case Study (JMV, JLÁM, JCRS, IR), pp. 54–60.
ICEIS-v2-2004-Poulet #data mining #towards #visual notation: Towards Visual Data Mining (FP), pp. 349–356.
ICEIS-v2-2004-TagarelliTG #clustering #linear #programming: Mining Scientific Results Through the Combined Use of Clustering and Linear Programming Techniques (AT, IT, SG), pp. 84–91.
ICEIS-v2-2004-UdechukwuBA #framework #performance: An Efficient Framework for Iterative Time-Series Trend Mining (AU, KB, RA), pp. 130–137.
ICEIS-v2-2004-ZarateAPR #data mining: Data Mining Application to Obtain Profiles of Patients with Nephrolithiasis (LEZ, PA, RP, TR), pp. 104–109.
ICEIS-v4-2004-LimaEMFC #data mining #information management #web: Archcollect Front-End: A Web Usage Data Mining Knowledge Acquisition Mechanism Focused on Static or Dynamic Contenting Applications (JdCL, AAAE, JGdM, BF, TGdSC), pp. 258–262.
ICEIS-v5-2004-BadjioP #data mining #tool support #usability #visual notation: Usability of Visual Data Mining Tools (EPFB, FP), pp. 254–258.
ICEIS-v5-2004-JantkeLGGTT #data mining #learning: Learning by Doing and Learning when Doing: Dovetailing E-Learning and Decision Support with a Data Mining Tutor (KPJ, SL, GG, PAG, BT, BT), pp. 238–241.
CIKM-2004-ChungJM #clustering #dataset #using: Mining gene expression datasets using density-based clustering (SC, JJ, DM), pp. 150–151.
CIKM-2004-Ramakrishnan: The EDAM project: mining mass spectra and more (RR), p. 1.
CIKM-2004-WangXY #biology #scalability #sequence: Scalable sequential pattern mining for biological sequences (KW, YX, JXY), pp. 178–187.
ICML-2004-NatteeSNO #first-order #learning #multi: Learning first-order rules from data with multiple parts: applications on mining chemical compound data (CN, SS, MN, TO).
ICPR-v2-2004-BouchaffraT #concept #design: Introduction to the Concept of Structural HMM: Application to Mining Customers’ Preferences in Automotive Design (DB, JT), pp. 493–496.
KDD-2004-AbajoDLC #case study #data mining #delivery #industrial #modelling #quality: ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study (NdA, ABD, VL, SRC), pp. 799–804.
KDD-2004-AgichteinG #automation #segmentation: Mining reference tables for automatic text segmentation (EA, VG), pp. 20–29.
KDD-2004-AksoyKTM #classification #image #interactive: Interactive training of advanced classifiers for mining remote sensing image archives (SA, KK, CT, GBM), pp. 773–782.
KDD-2004-CaruanaN #analysis #data mining #empirical #learning #metric #performance: Data mining in metric space: an empirical analysis of supervised learning performance criteria (RC, ANM), pp. 69–78.
KDD-2004-ChengYH #database #incremental #named #scalability: IncSpan: incremental mining of sequential patterns in large database (HC, XY, JH), pp. 527–532.
KDD-2004-DavidsonGST #algorithm #approach #data mining #matrix #quality: A general approach to incorporate data quality matrices into data mining algorithms (ID, AG, AS, GKT), pp. 794–798.
KDD-2004-EsterGJH #data mining #problem #segmentation: A microeconomic data mining problem: customer-oriented catalog segmentation (ME, RG, WJ, ZH), pp. 557–562.
KDD-2004-GadeWK #constraints #performance: Efficient closed pattern mining in the presence of tough block constraints (KG, JW, GK), pp. 138–147.
KDD-2004-HeCH #approach #correlation #interface #query #web: Discovering complex matchings across web query interfaces: a correlation mining approach (BH, KCCC, JH), pp. 148–157.
KDD-2004-Heckerman #data mining #modelling #visual notation: Graphical models for data mining (DH), p. 2.
KDD-2004-HorvathGW #graph #kernel #predict: Cyclic pattern kernels for predictive graph mining (TH, TG, SW), pp. 158–167.
KDD-2004-HuanWPY #database #graph #named: SPIN: mining maximal frequent subgraphs from graph databases (JH, WW, JP, JY), pp. 581–586.
KDD-2004-HuL: Mining and summarizing customer reviews (MH, BL), pp. 168–177.
KDD-2004-JehW #graph: Mining the space of graph properties (GJ, JW), pp. 187–196.
KDD-2004-JiangPRTZ #array #clustering: Mining coherent gene clusters from gene-sample-time microarray data (DJ, JP, MR, CT, AZ), pp. 430–439.
KDD-2004-JinZM #analysis #probability #semantics #web: Web usage mining based on probabilistic latent semantic analysis (XJ, YZ, BM), pp. 197–205.
KDD-2004-KantarciogluJC #data mining #privacy #question: When do data mining results violate privacy? (MK, JJ, CC), pp. 599–604.
KDD-2004-KeoghLR #data mining #towards: Towards parameter-free data mining (EJK, SL, C(R), pp. 206–215.
KDD-2004-LinKLLN #monitoring #visual notation: Visually mining and monitoring massive time series (JL, EJK, SL, JPL, DMN), pp. 460–469.
KDD-2004-MamoulisCKHTC #query: Mining, indexing, and querying historical spatiotemporal data (NM, HC, GK, MH, YT, DWC), pp. 236–245.
KDD-2004-NakataT #predict: Mining traffic data from probe-car system for travel time prediction (TN, JiT), pp. 817–822.
KDD-2004-NatsevNS #multi #representation #semantics: Semantic representation: search and mining of multimedia content (AN, MRN, JRS), pp. 641–646.
KDD-2004-NijssenK #difference: A quickstart in frequent structure mining can make a difference (SN, JNK), pp. 647–652.
KDD-2004-RamakrishnanKMPH #algorithm: Turning CARTwheels: an alternating algorithm for mining redescriptions (NR, DK, BM, MP, RFH), pp. 266–275.
KDD-2004-WangWPZS #database #graph #scalability: Scalable mining of large disk-based graph databases (CW, WW, JP, YZ, BS), pp. 316–325.
KDD-2004-WuGH #clustering #network #using: Mining scale-free networks using geodesic clustering (AYW, MG, JH), pp. 719–724.
KDD-2004-Yang #complexity: The complexity of mining maximal frequent itemsets and maximal frequent patterns (GY), pp. 344–353.
KDD-2004-YangLHG #named #performance #query #xml: 2PXMiner: an efficient two pass mining of frequent XML query patterns (LHY, MLL, WH, XG), pp. 731–736.
KDD-2004-ZhaiVY #comparative: A cross-collection mixture model for comparative text mining (CZ, AV, BY), pp. 743–748.
KDD-2004-ZhangMCS #performance: Fast mining of spatial collocations (XZ, NM, DWC, YS), pp. 384–393.
KDD-2004-ZhangZK #approach #category theory #data mining #image #modelling: A data mining approach to modeling relationships among categories in image collection (RZ, Z(Z, SK), pp. 749–754.
KDD-2004-ZhuL #data mining #privacy: Optimal randomization for privacy preserving data mining (MYZ, LL), pp. 761–766.
SIGIR-2004-LamHC #learning #similarity: Learning phonetic similarity for matching named entity translations and mining new translations (WL, RH, PSC), pp. 289–296.
SIGIR-2004-XuU #analysis #ranking #web: A unified model of literal mining and link analysis for ranking web resources (YX, KU), pp. 546–547.
ASE-2004-BreuK #using: Aspect Mining Using Event Traces (SB, JK), pp. 310–315.
ICSE-2004-ZimmermannWDZ #version control: Mining Version Histories to Guide Software Changes (TZ, PW, SD, AZ), pp. 563–572.
SAC-2004-AgyemangBA #framework #web: Framework for mining web content outliers (MA, KB, RA), pp. 590–594.
SAC-2004-Goethals #memory management: Memory issues in frequent itemset mining (BG), pp. 530–534.
SAC-2004-HuP #approach #data mining #database #detection: A data mining approach for database intrusion detection (YH, BP), pp. 711–716.
SAC-2004-KusumuraHN: Text mining agent for net auction (YK, YH, SN), pp. 1095–1102.
SAC-2004-OrlandoPS #algorithm #sequence: A new algorithm for gap constrained sequence mining (SO, RP, CS), pp. 540–547.
SAC-2004-QiW #set: A model for mining outliers from complex data sets (HQ, JW), pp. 595–599.
SAC-2004-Savinov #dependence: Mining dependence rules by finding largest itemset support quota (AAS), pp. 525–529.
SAC-2004-ShangSG #generative #sql: SQL based frequent pattern mining without candidate generation (XS, KUS, IG), pp. 618–619.
HPDC-2004-GilburdSW #data mining #privacy: Privacy-Preserving Data Mining on Data Grids in the Presence of Malicious Participants (BG, AS, RW), pp. 225–234.
PDP-2004-BorzemskiLN #analysis #data mining #internet #performance: Application of Data Mining for the Analysis of Internet Path Performance (LB, LL, ZN), pp. 54–59.
DRR-2003-YangL #image #retrieval #semantics: Semantics-based image retrieval by text mining on environmental texts (HCY, CHL), pp. 266–277.
JCDL-2003-LeroyCMEFKHLXMN #data mining #named: Genescene: Biomedical Text And Data Mining (GL, HC, JDM, SE, RRF, KLK, ZH, JL, JJX, DM, TGN), pp. 116–118.
PODS-2003-EvfimievskiGS #data mining #privacy: Limiting privacy breaches in privacy preserving data mining (AVE, JG, RS), pp. 211–222.
PODS-2003-RameshMZ #data mining #theory and practice: Feasible itemset distributions in data mining: theory and application (GR, WM, MJZ), pp. 284–295.
VLDB-2003-HinneburgLH #data mining #database #named: COMBI-Operator: Database Support for Data Mining Applications (AH, WL, DH), pp. 429–439.
VLDB-2003-NieKH #effectiveness #integration #named #statistics #using: BibFinder/StatMiner: Effectively Mining and Using Coverage and Overlap Statistics in Data Integration (ZN, SK, TH), pp. 1097–1100.
VLDB-2003-PapadimitriouBF #adaptation: Adaptive, Hands-Off Stream Mining (SP, AB, CF), pp. 560–571.
VLDB-2003-TengCY #data type: A Regression-Based Temporal Pattern Mining Scheme for Data Streams (WGT, MSC, PSY), pp. 93–104.
VLDB-2003-WangZL #data mining #data type #named #sql: ATLAS: A Small but Complete SQL Extension for Data Mining and Data Streams (HW, CZ, CL), pp. 1113–1116.
VLDB-2003-YangLH #performance #query #xml: Efficient Mining of XML Query Patterns for Caching (LHY, MLL, WH), pp. 69–80.
ICSM-2003-BalanyiF #c++ #design pattern #source code: Mining Design Patterns from C++ Source Code (ZB, RF), pp. 305–314.
ICSM-2003-Sayyad-ShirabadLM #legacy #maintenance: Mining the Maintenance History of a Legacy Software System (JSS, TCL, SM), pp. 95–104.
IWPC-2003-TjortjisSL #comprehension #source code: Facilitating Program Comprehension by Mining Association Rules from Source Code (CT, LS, PJL), pp. 125–133.
ICEIS-v2-2003-DoP #algorithm #dataset #scalability: Mining Very Large Datasets with Support Vector Machine Algorithms (TND, FP), pp. 140–147.
ICEIS-v2-2003-FernedaPS: Text Mining for Organizational Intelligence (EF, HAdP, EMS), pp. 446–450.
ICEIS-v2-2003-GalianoCMSB #data mining #usability: Usability Issues in Data Mining Systems (FBG, JCC, NM, JMS, IJB), pp. 418–421.
ICEIS-v2-2003-KrolikowskiMP #data mining #query: Set-Oriented Indexes for Data Mining Queries (ZK, MM, JP), pp. 316–323.
ICEIS-v2-2003-KuusikL #approach #data mining #using: An Approach of Data Mining Using Monotone Systems (RK, GL), pp. 482–485.
ICEIS-v2-2003-MaciasVSR #data mining #development: A Data Mining Method to Support Decision Making in Software Development Projects (JLÁM, JMV, JCRS, IR), pp. 11–18.
ICEIS-v2-2003-PetitP #approach #data mining: A New Approach of Data Mining: The Meta Projectories (CP, SP), pp. 515–518.
ICEIS-v2-2003-SaravananR #summary: Text Summarization: An Upcoming Tool in Text Mining (MS, SR), pp. 541–544.
ICEIS-v2-2003-SrikumarB #algorithm #set #transaction: An Algorithm for Mining Maximal Frequent Sets Based on Dominancy of Transactions (KS, BB), pp. 422–425.
ICEIS-v2-2003-WangRLC #online #realtime #recommendation #web: Mining Web Usage Data for Real-Time Online Recommendation (MW, SJR, SYL, JKYC), pp. 575–578.
ICEIS-v3-2003-HoangHB #data mining #detection: Intrusion Detection Based on Data Mining (XDH, JH, PB), pp. 341–346.
CIKM-2003-LinK #using #web: Question answering from the web using knowledge annotation and knowledge mining techniques (JJL, BK), pp. 116–123.
CIKM-2003-SunL #web: Web unit mining: finding and classifying subgraphs of web pages (AS, EPL), pp. 108–115.
CIKM-2003-TangZ #multi: Mining multiple phenotype structures underlying gene expression profiles (CT, AZ), pp. 418–425.
KDD-2003-Aggarwal #data mining #design #distance #towards: Towards systematic design of distance functions for data mining applications (CCA), pp. 9–18.
KDD-2003-ArgamonSS #multi: Style mining of electronic messages for multiple authorship discrimination: first results (SA, MS, SSS), pp. 475–480.
KDD-2003-BayS #linear: Mining distance-based outliers in near linear time with randomization and a simple pruning rule (SDB, MS), pp. 29–38.
KDD-2003-BhatnagarKN #classification: Mining high dimensional data for classifier knowledge (RB, GK, WN), pp. 481–486.
KDD-2003-DuZ #data mining #privacy #random #using: Using randomized response techniques for privacy-preserving data mining (WD, JZZ), pp. 505–510.
KDD-2003-El-HajjZ #dataset #interactive #matrix #performance #scalability: Inverted matrix: efficient discovery of frequent items in large datasets in the context of interactive mining (MEH, ORZ), pp. 109–118.
KDD-2003-EtzioniTKY: To buy or not to buy: mining airfare data to minimize ticket purchase price (OE, RT, CAK, AY), pp. 119–128.
KDD-2003-FramAD #data mining #empirical #safety: Empirical Bayesian data mining for discovering patterns in post-marketing drug safety (DMF, JSA, WD), pp. 359–368.
KDD-2003-GamaRM #data type #performance: Accurate decision trees for mining high-speed data streams (JG, RR, PM), pp. 523–528.
KDD-2003-HoNKLNYT #abstraction: Mining hepatitis data with temporal abstraction (TBH, TDN, SK, SQL, DN, HY, KT), pp. 369–377.
KDD-2003-HsuDL #database #image: Mining viewpoint patterns in image databases (WH, JD, MLL), pp. 553–558.
KDD-2003-LastFK #approach #automation #data mining #testing: The data mining approach to automated software testing (ML, MF, AK), pp. 388–396.
KDD-2003-LiuGZ #web: Mining data records in Web pages (BL, RLG, YZ), pp. 601–606.
KDD-2003-MorinagaYT #distributed: Distributed cooperative mining for information consortia (SM, KY, JiT), pp. 619–624.
KDD-2003-SequeiraZSC #data mining #locality #source code: Improving spatial locality of programs via data mining (KS, MJZ, BKS, CDC), pp. 649–654.
KDD-2003-TangZP: Mining phenotypes and informative genes from gene expression data (CT, AZ, JP), pp. 655–660.
KDD-2003-TaoMF #framework #using: Weighted Association Rule Mining using weighted support and significance framework (FT, FM, MMF), pp. 661–666.
KDD-2003-WangFYH #classification #concept #data type #using: Mining concept-drifting data streams using ensemble classifiers (HW, WF, PSY, JH), pp. 226–235.
KDD-2003-WangHP: CLOSET+: searching for the best strategies for mining frequent closed itemsets (JW, JH, JP), pp. 236–245.
KDD-2003-WangJL: Mining unexpected rules by pushing user dynamics (KW, YJ, LVSL), pp. 246–255.
KDD-2003-WeissBKD #data mining #knowledge-based: Knowledge-based data mining (SMW, SJB, SK, SD), pp. 456–461.
KDD-2003-YanH #graph #named: CloseGraph: mining closed frequent graph patterns (XY, JH), pp. 286–295.
KDD-2003-YiLL #data mining #web: Eliminating noisy information in Web pages for data mining (LY, BL, XL), pp. 296–305.
KDD-2003-ZakiG #performance #using: Fast vertical mining using diffsets (MJZ, KG), pp. 326–335.
KDD-2003-ZhangSY #data mining: Applying data mining in investigating money laundering crimes (Z(Z, JJS, PSY), pp. 747–752.
MLDM-2003-AntunesO #constraints: Generalization of Pattern-Growth Methods for Sequential Pattern Mining with Gap Constraints (CA, ALO), pp. 239–251.
MLDM-2003-Bunke #data mining #graph #machine learning #tool support: Graph-Based Tools for Data Mining and Machine Learning (HB), pp. 7–19.
MLDM-2003-ChiuX #optimisation: Optimizing Financial Portfolios from the Perspective of Mining Temporal Structures of Stock Returns (KCC, LX), pp. 266–275.
MLDM-2003-KayaA: Integrating Fuzziness with OLAP Association Rules Mining (MK, RA), pp. 353–368.
MLDM-2003-LeleuRBE #dataset #named: GO-SPADE: Mining Sequential Patterns over Datasets with Consecutive Repetitions (ML, CR, JFB, GE), pp. 293–306.
SEKE-2003-ChapinK #data mining #metric #re-engineering: Validative measurement in software engineering: a data mining example (NC, MKM), pp. 626–633.
SEKE-2003-LaiLB #data access #database #object-oriented: Mining Access Patterns for Enhancing Navigational Access in Object-Oriented Database (CL, SL, JB), pp. 679–684.
SEKE-2003-LaiSF #realtime: Real-Time Mining of Partial Periodic Patterns (CL, LS, MF), pp. 259–266.
SEKE-2003-WuS #approach #data mining: A Data Mining Approach for Dynamic Software Project Plan Tracking (CSW, DBS), pp. 634–638.
PADL-2003-ClareK #data mining #functional #lazy evaluation: Data Mining the Yeast Genome in a Lazy Functional Language (AC, RDK), pp. 19–36.
PADL-2003-Page #biology #database #declarative: The Role of Declarative Languages in Mining Biological Databases (CDPJ), p. 1.
SAC-2003-BarbaraLLJC #data mining #detection: Bootstrapping a Data Mining Intrusion Detection System (DB, YL, JLL, SJ, JC), pp. 421–425.
SAC-2003-Ferrer-TroyanoAS #data type #prototype: Prototype-based Mining of Numeric Data Streams (FJFT, JSAR, JCRS), pp. 480–484.
SAC-2003-HuaJVT #algebra #analysis #approach #data mining #named #performance #using: ADMiRe: An Algebraic Approach to System Performance Analysis Using Data Mining Techniques (KAH, NJ, RV, DAT), pp. 490–496.
SAC-2003-HuangXSP: Mining Confident Colocation Rules without A Support Threshold (YH, HX, SS, JP), pp. 497–501.
SAC-2003-JiaPP #constraints: Tough Constraint-Based Frequent Closed Itemsets Mining (LJ, RP, DP), pp. 416–420.
SAC-2003-Lin: Mining Maximal Frequent Intervals (JLL), pp. 426–431.
SAC-2003-LiZO #data mining #distributed #modelling #similarity: A New Distributed Data Mining Model Based on Similarity (TL, SZ, MO), pp. 432–436.
SAC-2003-Meo #data mining #optimisation: Optimization of a Language for Data Mining (RM), pp. 437–444.
SAC-2003-NenadicSA: Terminology-driven Mining of Biomedical Literature (GN, IS, SA), pp. 83–87.
SAC-2003-TsengT #mobile #performance #web: An Efficient Method for Mining Associated Service Patterns in Mobile Web Environments (SMT, CFT), pp. 455–459.
PPoPP-2003-Kazar #data mining #performance #scalability: High performance spatial data mining for very large data-sets (BMK), p. 1.
SIGMOD-2002-DasuJMS #database #how #quality: Mining database structure; or, how to build a data quality browser (TD, TJ, SM, VS), pp. 240–251.
SIGMOD-2002-GarofalakisGR #data type #query #tutorial: Querying and mining data streams: you only get one look a tutorial (MNG, JG, RR), p. 635.
SIGMOD-2002-YangWYH: Mining long sequential patterns in a noisy environment (JY, WW, PSY, JH), pp. 406–417.
VLDB-2002-Chakrabarti #fine-grained: Searching and Mining Fine-Grained Semi-Structured Data (SC).
VLDB-2002-Faloutsos #analysis #data mining #similarity: Sensor Data Mining: Similarity Search and Pattern Analysis (CF).
VLDB-2002-GarofalakisG #data type #query: Querying and Mining Data Streams: You Only Get One Look (MNG, JG).
VLDB-2002-OhuraTPK #internet #query #using #web: Experiments on Query Expansion for Internet Yellow Page Services Using Web Log Mining (YO, KT, IP, MK), pp. 1008–1018.
VLDB-2002-RizviH #maintenance #privacy: Maintaining Data Privacy in Association Rule Mining (SR, JRH), pp. 682–693.
IWPC-2002-El-RamlySS #case study #interactive #modelling: Mining System-User Interaction Traces for Use Case Models (MER, ES, PGS), pp. 21–29.
ICALP-2002-Mannila #data mining #problem: Local and Global Methods in Data Mining: Basic Techniques and Open Problems (HM), pp. 57–68.
ICEIS-2002-CarrascoMG #data mining #flexibility #named #query: FSQL: A Flexible Query Language for Data Mining (RAC, MAVM, JG), pp. 50–56.
ICEIS-2002-KrishnaswamyLZ #data mining #distributed #optimisation #predict #runtime: Supporting the Optimisation of Distributed Data Mining by Predicting Application Run Times (SK, SWL, ABZ), pp. 374–381.
ICEIS-2002-LiK #e-commerce #framework: Intelligent Agent-Based Framework for Mining Customer Buying Habits in E-Commerce (QL, RK), pp. 1016–1022.
ICEIS-2002-MengYCC #data mining #information management: Data Mining Mechanisms in Knowledge Management System (IHM, WPY, WCC, LPC), pp. 399–404.
ICEIS-2002-SanchezSVACD #data mining #using: Using Data Mining Techniques to Analyze Correspondences between Partitions (DS, JMS, MAVM, VA, JC, GD), pp. 179–186.
ICEIS-2002-SantosNASR #classification #data mining #database #learning #using: Augmented Data Mining over Clinical Databases Using Learning Classifier Systems (MFS, JN, AA, ÁMS, FR), pp. 512–516.
ICEIS-2002-TanTS #data mining #parallel #performance #taxonomy: A Taxonomy for Inter-Model Parallelism in High Performance Data Mining (LT, DT, KAS), pp. 534–539.
CIKM-2002-Faloutsos #data mining #network #self: Future directions in data mining: streams, networks, self-similarity and power laws (CF), p. 93.
CIKM-2002-KaoCLH #analysis #web: Entropy-based link analysis for mining web informative structures (HYK, MSC, SHL, JMH), pp. 574–581.
CIKM-2002-MotoyoshiMW: Mining temporal classes from time series data (MM, TM, KW), pp. 493–498.
CIKM-2002-NahmM: Mining soft-matching association rules (UYN, RJM), pp. 681–683.
CIKM-2002-NieNVK #statistics: Mining coverage statistics for websource selection in a mediator (ZN, UN, SV, SK), pp. 678–680.
CIKM-2002-PanF #data mining #library #quote #video: “GeoPlot”: spatial data mining on video libraries (JYP, CF), pp. 405–412.
CIKM-2002-PeiHW #constraints #database #scalability: Mining sequential patterns with constraints in large databases (JP, JH, WW), pp. 18–25.
ICML-2002-WuZZ: Mining Both Positive and Negative Association Rules (XW, CZ, SZ), pp. 658–665.
ICPR-v3-2002-HongH #multimodal: Multimodal Temporal Pattern Mining (PH, TSH), pp. 465–472.
KDD-2002-Aggarwal02a #case study #collaboration #crawling #experience #resource management #topic #user interface: Collaborative crawling: mining user experiences for topical resource discovery (CCA), pp. 423–428.
KDD-2002-AlqallafKMZ #correlation #data mining #robust #scalability: Scalable robust covariance and correlation estimates for data mining (FAA, KPK, RDM, RHZ), pp. 14–23.
KDD-2002-AyresFGY #representation #using: Sequential PAttern mining using a bitmap representation (JA, JF, JG, TY), pp. 429–435.
KDD-2002-El-RamlySS #approach #behaviour #runtime: From run-time behavior to usage scenarios: an interaction-pattern mining approach (MER, ES, PGS), pp. 315–324.
KDD-2002-EsterKS #web: Web site mining: a new way to spot competitors, customers and suppliers in the world wide web (ME, HPK, MS), pp. 249–258.
KDD-2002-EvfimievskiSAG #privacy: Privacy preserving mining of association rules (AVE, RS, RA, JG), pp. 217–228.
KDD-2002-HultenD #constant #database #modelling #scalability: Mining complex models from arbitrarily large databases in constant time (GH, PMD), pp. 525–531.
KDD-2002-JulischD #detection: Mining intrusion detection alarms for actionable knowledge (KJ, MD), pp. 366–375.
KDD-2002-KeoghK #benchmark #data mining #empirical #metric #on the #overview: On the need for time series data mining benchmarks: a survey and empirical demonstration (EJK, SK), pp. 102–111.
KDD-2002-LiangK #network: Mining heterogeneous gene expression data with time lagged recurrent neural networks (YL, AK), pp. 415–421.
KDD-2002-LinLCY #data mining #database #distributed #transaction: Distributed data mining in a chain store database of short transactions (CRL, CHL, MSC, PSY), pp. 576–581.
KDD-2002-LittleJLRS #data mining: Collusion in the U.S. crop insurance program: applied data mining (BBL, WLJ, ACL, RMR, SAS), pp. 594–598.
KDD-2002-LiuL #adaptation #classification #documentation #incremental: Incremental context mining for adaptive document classification (RLL, YLL), pp. 599–604.
KDD-2002-LiuPWH #set: Mining frequent item sets by opportunistic projection (JL, YP, KW, JH), pp. 229–238.
KDD-2002-MorinagaYTF #web: Mining product reputations on the Web (SM, KY, KT, TF), pp. 341–349.
KDD-2002-PalmerGF #data mining #graph #named #performance #scalability: ANF: a fast and scalable tool for data mining in massive graphs (CRP, PBG, CF), pp. 81–90.
KDD-2002-RichardsonD: Mining knowledge-sharing sites for viral marketing (MR, PMD), pp. 61–70.
KDD-2002-SequeiraZ #data mining #named: ADMIT: anomaly-based data mining for intrusions (KS, MJZ), pp. 386–395.
KDD-2002-VaidyaC #privacy: Privacy preserving association rule mining in vertically partitioned data (JV, CC), pp. 639–644.
KDD-2002-WuFS #approach #classification #data mining #named: B-EM: a classifier incorporating bootstrap with EM approach for data mining (XW, JF, KRS), pp. 670–675.
KDD-2002-Zaki: Efficiently mining frequent trees in a forest (MJZ), pp. 71–80.
SEKE-2002-PoleseTT #data mining: A data mining based system supporting tactical decisions (GP, MT, GT), pp. 681–684.
SIGIR-2002-ChoudhariDJMMPR #named #ontology #web: YellowPager: a tool for ontology-based mining of service directories from web sources (PC, HD, AJ, AM, SM, SP, IVR), p. 458.
SPLC-2002-SmithBB #analysis #component #product line #re-engineering #using: Using the Options Analysis for Reengineering (OAR) Method for Mining Components for a Product Line (DBS, LO, JB), pp. 316–327.
POPL-2002-AmmonsBL #specification: Mining specifications (GA, RB, JRL), pp. 4–16.
SAC-2002-ChangJ #clustering #data mining #scalability: A new cell-based clustering method for large, high-dimensional data in data mining applications (JWC, DSJ), pp. 503–507.
SAC-2002-Geist #data mining #framework: A framework for data mining and KDD (IG), pp. 508–513.
SAC-2002-KrishnaswamyLZ #data mining #estimation #metric #quality #runtime: Application run time estimation: a quality of service metric for web-based data mining services (SK, SWL, ABZ), pp. 1153–1159.
SAC-2002-MaciasVR #algorithm #using: Mining interesting regions using an evolutionary algorithm (JLÁM, JMV, JCRS), pp. 498–502.
SAC-2002-WangW #approach #data mining #optimisation #query #relational: Optimizing relational store for e-catalog queries: a data mining approach (MW, XSW), pp. 1147–1152.
DAC-2002-LiuSRC #data mining #design #megamodelling #scalability: Remembrance of circuits past: macromodeling by data mining in large analog design spaces (HL, AS, RAR, LRC), pp. 437–442.
WICSA-2001-StoermerO #architecture #named #product line: MAP — Mining Architectures for Product Line Evaluations (CS, LO), pp. 35–44.
JCDL-2001-PanFV #classification #named #video: VideoGraph: a new tool for video mining and classification (JYP, CF), pp. 116–117.
PODS-2001-AgrawalA #algorithm #data mining #design #on the #privacy #quantifier: On the Design and Quantification of Privacy Preserving Data Mining Algorithms (DA, CCA).
VLDB-2001-DongHLPW #multi: Mining Multi-Dimensional Constrained Gradients in Data Cubes (GD, JH, JMWL, JP, KW), pp. 321–330.
VLDB-2001-MargaritisFT #data mining #named #performance #scalability: NetCube: A Scalable Tool for Fast Data Mining and Compression (DM, CF, ST), pp. 311–320.
VLDB-2001-SadriZZA #data mining #query: A Sequential Pattern Query Language for Supporting Instant Data Mining for e-Services (RS, CZ, AMZ, JA), pp. 653–656.
ICSM-2001-ShirabadLM #maintenance: Supporting Software Maintenance by Mining Software Update Records (JSS, TCL, SM), pp. 22–31.
ICEIS-v1-2001-HippGG #algorithm #database #relational: Integrating Association Rule Mining Algorithms with Relational Database Systems (JH, UG, UG), pp. 130–137.
ICEIS-v1-2001-ThorntonR #artificial reality #data mining #network #using: Using Virtual Reality Data Mining for Network Management (KEBT, CR), pp. 340–344.
CIKM-2001-DasNW #agile: Rapid Association Rule Mining (AD, WKN, YKW), pp. 474–481.
CIKM-2001-GhaniJM #corpus #web: Mining the Web to Create Minority Language Corpora (RG, RJ, DM), pp. 279–286.
CIKM-2001-KrishnaK #algorithm #clustering #symmetry: A Clustering Algorithm for Asymmetrically Related Data with Applications to Text Mining (KK, RK), pp. 571–573.
CIKM-2001-LeeLC #algorithm #incremental #performance: Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining (CHL, CRL, MSC), pp. 263–270.
CIKM-2001-NanavatiCJK: Mining Generalised Disjunctive Association Rules (AAN, KPC, SJ, RK), pp. 482–489.
CIKM-2001-PintoHPWCD #multi: Multi-Dimensional Sequential Pattern Mining (HP, JH, JP, KW, QC, UD), pp. 81–88.
CIKM-2001-RadevQZBZFP #natural language #web: Mining the Web for Answers to Natural Language Questions (DRR, HQ, ZZ, SBG, ZZ, WF, JMP), pp. 143–150.
CIKM-2001-WangHCC: Mining Confident Rules Without Support Requirement (KW, YH, DWLC, FYLC), pp. 89–96.
KDD-2001-AdderleyM #behaviour #case study #commit #data mining #modelling: Data mining case study: modeling the behavior of offenders who commit serious sexual assaults (RA, PBM), pp. 215–220.
KDD-2001-AggarwalP #concept #re-engineering #semistructured data #set: Mining massively incomplete data sets by conceptual reconstruction (CCA, SP), pp. 227–232.
KDD-2001-BiFK: The “DGX” distribution for mining massive, skewed data (ZB, CF, FK), pp. 17–26.
KDD-2001-BujaL #classification #data mining: Data mining criteria for tree-based regression and classification (AB, YSL), pp. 27–36.
KDD-2001-DittrichS #algorithm #named #scalability #set: GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces (JPD, BS), pp. 47–56.
KDD-2001-DomingosR #network: Mining the network value of customers (PMD, MR), pp. 57–66.
KDD-2001-Edelstein #data mining #question: Data mining: are we there yet? (HE), p. 7.
KDD-2001-Elkan #challenge #data mining #lessons learnt: Magical thinking in data mining: lessons from CoIL challenge 2000 (CE), pp. 426–431.
KDD-2001-GarckeG #data mining #using: Data mining with sparse grids using simplicial basis functions (JG, MG), pp. 87–96.
KDD-2001-HueglinV #data mining: Data mining techniques to improve forecast accuracy in airline business (CH, FV), pp. 438–442.
KDD-2001-HultenSD #data type: Mining time-changing data streams (GH, LS, PMD), pp. 97–106.
KDD-2001-JinTH #database #scalability: Mining top-n local outliers in large databases (WJ, AKHT, JH), pp. 293–298.
KDD-2001-Kohavi #e-commerce: Mining e-commerce data: the good, the bad, and the ugly (RK), pp. 8–13.
KDD-2001-KramerRH: Molecular feature mining in HIV data (SK, LDR, CH), pp. 136–143.
KDD-2001-LambertP #transaction: Mining a stream of transactions for customer patterns (DL, JCP), pp. 305–310.
KDD-2001-LiY: Mining from open answers in questionnaire data (HL, KY), pp. 443–449.
KDD-2001-MahHL #network: Funnel report mining for the MSN network (TM, HH, YL), pp. 450–455.
KDD-2001-Morimoto #database #set: Mining frequent neighboring class sets in spatial databases (YM), pp. 353–358.
KDD-2001-Netz #data mining #database #developer #framework #platform: Data mining platform for database developers (AN), p. 14.
KDD-2001-Ramakrishnan #collaboration #data mining: Mass collaboration and data mining (RR), p. 4.
KDD-2001-TrainaTPF #data mining #multi #named #scalability #tool support: Tri-plots: scalable tools for multidimensional data mining (AJMT, CTJ, SP, CF), pp. 184–193.
KDD-2001-WarnerRDB #interactive #knowledge base #web: Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web (DW, JNR, SDD, BB), pp. 467–472.
KDD-2001-YangWY #named: Infominer: mining surprising periodic patterns (JY, WW, PSY), pp. 395–400.
KDD-2001-YangZL #modelling #predict #web: Mining web logs for prediction models in WWW caching and prefetching (QY, HHZ, ITYL), pp. 473–478.
KDD-T-2001-FayyadRB #data mining #enterprise: E-business enterprise data mining (UMF, NR, PSB), pp. 1–85.
KDD-T-2001-GallantPT #data mining #web: Value-based data mining and web mining for CRM (SG, GPS, MT), pp. 325–390.
KDD-T-2001-HanLP #bibliography #perspective #scalability: Scalable frequent-pattern mining methods: an overview (JH, LVSL, JP), pp. 264–324.
KDD-T-2001-KarguptaJ #data mining #distributed #mobile #ubiquitous: Data mining “to go”: ubiquitous KDD for mobile and distributed environments (HK, AJ), pp. 186–263.
KDD-T-2001-Martin #data mining #robust #statistics: Data mining for outliers with robust statistics (RDM), pp. 86–118.
LSO-2001-KrishnaswamyLZ #data mining #elicitation: Knowledge Elicitation through Web-Based Data Mining Services (SK, SWL, ABZ), pp. 120–134.
LSO-2001-VossRMJ #collaboration #data mining #enterprise: Collaboration Support for Virtual Data Mining Enterprises (AV, GR, SM, AJ), pp. 83–95.
MLDM-2001-PernerB #data mining #hybrid: A Hybrid Tool for Data Mining in Picture Archiving System (PP, TPB), pp. 141–156.
MLDM-2001-SackK #data mining #evaluation: Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining (US, MK), pp. 12–22.
MLDM-2001-SyG #analysis #approach #data mining #statistics: Data Mining Approach Based on Information-Statistical Analysis: Application to Temporal-Spatial Data (BKS, AKG), pp. 128–140.
MLDM-2001-Visa: Technology of Text Mining (AV), pp. 1–11.
SEKE-2001-AlonsoCGM #data mining: Combining Expert Knowledge and Data Mining in a Medical Diagnosis Domain (FA, JPCV, ÁLG, CM), pp. 412–419.
SEKE-2001-ConciMC #image: Image Mining by Color Coateat (AC, EMMMC), pp. 405–411.
SIGIR-2001-LuLC #query: Anchor Text Mining for Translation Extraction of Query Terms (WHL, HJL, LFC), pp. 388–389.
TOOLS-USA-2001-LiKLCL #algorithm #automation #data mining #parallel: Automatic Data Mining by Asynchronous Parallel Evolutionary Algorithms (JL, ZK, YL, HC, PL), pp. 99–107.
ICSE-2001-Michail #data mining #library #named #reuse: CodeWeb: Data Mining Library Reuse Patterns (AM), pp. 827–828.
ICSE-2001-SmithOB #analysis #architecture #component #product line #re-engineering: Mining Components for a Software Architecture and a Product Line: the Options Analysis for Reengineering (OAR) Method (DBS, LO, JB), p. 728.
HPDC-2001-KuntrarukP #data mining #distributed #feature model #parallel #using: Massively Parallel Distributed Feature Extraction in Textual Data Mining Using HDDI(tm) (JK, WMP), pp. 363–370.
SIGMOD-2000-AgrawalS #data mining #privacy: Privacy-Preserving Data Mining (RA, RS), pp. 439–450.
SIGMOD-2000-HanPY #generative: Mining Frequent Patterns without Candidate Generation (JH, JP, YY), pp. 1–12.
SIGMOD-2000-HsuLG #image #information management: Image Mining in IRIS: Integrated Retinal Information System (WH, MLL, KGG), p. 593.
SIGMOD-2000-PalmerF #clustering #data mining: Density Biased Sampling: An Improved Method for Data Mining and Clustering (CRP, CF), pp. 82–92.
SIGMOD-2000-PeiMHZ #benchmark #data mining #metric #performance #towards: Towards Data Mining Benchmarking: A Testbed for Performance Study of Frequent Pattern Mining (JP, RM, KH, HZ), p. 592.
SIGMOD-2000-RamaswamyRS #algorithm #performance #scalability #set: Efficient Algorithms for Mining Outliers from Large Data Sets (SR, RR, KS), pp. 427–438.
SIGMOD-2000-RiedelFGN #data mining #for free: Data Mining on an OLTP System (Nearly) for Free (ER, CF, GRG, DN), pp. 13–21.
SIGMOD-2000-ShenoyHSBBS #database #scalability: Turbo-charging Vertical Mining of Large Databases (PS, JRH, SS, GB, MB, DS), pp. 22–33.
SIGMOD-2000-SzalayGKT #design #multi #overview: Designing and Mining Multi-Terabyte Astronomy Archives: The Sloan Digital Sky Survey (ASS, PZK, AT, JG, DRS, RJB), pp. 451–462.
VLDB-2000-ChakrabartiSST #collaboration #named: Memex: A Browsing Assistant for Collaborative Archiving and Mining of Surf Trails (SC, SS, MS, MT), pp. 603–606.
VLDB-2000-ChoenniV #algorithm #data mining #design #implementation: Design and Implementation of a Genetic-Based Algorithm for Data Mining (SC), pp. 33–42.
VLDB-2000-LakshmananJN #algebra #data mining: The 3W Model and Algebra for Unified Data Mining (TJ, LVSL, RTN), pp. 21–32.
VLDB-2000-NetzCBF #data mining #database #integration: Integration of Data Mining with Database Technology (AN, SC, JB, UMF), pp. 719–722.
VLDB-2000-Tsur #data mining: Data Mining in the Bioinformatics Domain (ST), pp. 711–714.
VLDB-2000-WangHH #constraints #using: Mining Frequent Itemsets Using Support Constraints (KW, YH, JH), pp. 43–52.
CSMR-2000-SartipiKM #architecture #data mining #design #using: Architectural Design Recovery using Data Mining Techniques (KS, KK, FM), pp. 129–140.
CIKM-2000-Zaki #category theory #constraints #sequence: Sequence Mining in Categorical Domains: Incorporating Constraints (MJZ), pp. 422–429.
ICML-2000-MamitsukaA #database #learning #performance #query #scalability: Efficient Mining from Large Databases by Query Learning (HM, NA), pp. 575–582.
ICPR-v1-2000-YouB #data mining #retrieval: Dynamic Shape Retrieval by Hierarchical Curve Matching, Snakes and Data Mining (JY, PB), pp. 5035–5038.
KDD-2000-Bay #multi #set: Multivariate discretization of continuous variables for set mining (SDB), pp. 315–319.
KDD-2000-BecherBF #automation #data analysis #data mining #performance: Automating exploratory data analysis for efficient data mining (JDB, PB, EF), pp. 424–429.
KDD-2000-Bhattacharyya #algorithm #data mining #modelling #multi #performance: Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing (SB), pp. 465–473.
KDD-2000-BrijsGSVW #data mining #framework: A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model (TB, BG, GS, KV, GW), pp. 300–304.
KDD-2000-Catlett #data mining #privacy: Among those dark electronic mills: privacy and data mining (JC), p. 4.
KDD-2000-DhondGV #data mining #optimisation: Data mining techniques for optimizing inventories for electronic commerce (AD, AG, SV), pp. 480–486.
KDD-2000-DomingosH #data type #performance: Mining high-speed data streams (PMD, GH), pp. 71–80.
KDD-2000-FountainDS #testing: Mining IC test data to optimize VLSI testing (TF, TGD, BS), pp. 18–25.
KDD-2000-GardnerB #data mining #problem: Data mining solves tough semiconductor manufacturing problems (MG, JB), pp. 376–383.
KDD-2000-GavrilovAIM #question: Mining the stock market (extended abstract): which measure is best? (MG, DA, PI, RM), pp. 487–496.
KDD-2000-HanPMCDH #named: FreeSpan: frequent pattern-projected sequential pattern mining (JH, JP, BMA, QC, UD, MH), pp. 355–359.
KDD-2000-HsuLLL #database: Exploration mining in diabetic patients databases: findings and conclusions (WH, MLL, BL, TWL), pp. 430–436.
KDD-2000-KingKCD #data mining #functional #predict #sequence #using: Genome scale prediction of protein functional class from sequence using data mining (RDK, AK, AC, LD), pp. 384–389.
KDD-2000-MaLWYL #data mining #student #using: Targeting the right students using data mining (YM, BL, CKW, PSY, SML), pp. 457–464.
KDD-2000-Papadimitriou #data mining #on the: On certain rigorous approaches to data mining (CHP), p. 2.
KDD-2000-PeiH #constraints #question: Can we push more constraints into frequent pattern mining? (JP, JH), pp. 350–354.
KDD-2000-PenaFL #behaviour #data mining #detection: Data mining to detect abnormal behavior in aerospace data (JMP, FF, SL), pp. 390–397.
KDD-2000-Stodder #data mining: After the gold rush (invited talk, abstract only): data mining in the new economy (DS), p. 7.
KDD-2000-TanBHG #data mining: Textual data mining of service center call records (PNT, HB, SAH, RPG), pp. 417–423.
KDD-2000-WangMSW #biology #case study #classification #data mining #network #sequence: Application of neural networks to biological data mining: a case study in protein sequence classification (JTLW, QM, DS, CHW), pp. 305–309.
KDD-2000-WangYY #performance: Efficient mining of weighted association rules (WAR) (WW, JY, PSY), pp. 270–274.
KDD-2000-YangWY: Mining asynchronous periodic patterns in time series data (JY, WW, PSY), pp. 275–279.
PADL-2000-HuCT #algorithm #analysis #data mining: Calculating a New Data Mining Algorithm for Market Basket Analysis (ZH, WNC, MT), pp. 169–184.
ICSE-2000-Michail #data mining #library #reuse #using: Data mining library reuse patterns using generalized association rules (AM), pp. 167–176.
SAC-2000-DongPDZ: The Application of Association Rule Mining to Remotely Sensed Data (JD, WP, QD, JZ), pp. 340–345.
SAC-2000-GoodwinM #data mining #predict: Data Mining for Preterm Birth Prediction (LKG, SM), pp. 46–51.
SAC-2000-HongKCW #algorithm #data-driven #database #fuzzy: Mining Fuzzy Rules from Quantitative Data Based on the AprioriTid Algorithm (TPH, CSK, SCC, SLW), pp. 534–536.
SAC-2000-PsailaL: Hierarchy-based Mining of Association Rules in Data Warehouses (GP, PLL), pp. 307–312.
SAC-2000-WangTH #database #dependence #functional #fuzzy #relational: Mining Functional Dependencies from Fuzzy Relational Databases (SLW, JST, TPH), pp. 490–493.
HPDC-2000-HinkeN #data mining #grid #power management: Data Mining on NASA’s Information Power Grid (THH, JN), pp. 292–293.
CL-2000-BastidePTSL #using: Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets (YB, NP, RT, GS, LL), pp. 972–986.
SIGMOD-1999-Chakrabarti #data mining #database #hypermedia: Hypertext Databases and Data Mining (SC), p. 508.
SIGMOD-1999-Hidber #online: Online Association Rule Mining (CH), pp. 145–156.
SIGMOD-1999-NgLHM #query #set: Exploratory Mining via Constrained Frequent Set Queries (RTN, LVSL, JH, TM), pp. 556–558.
VLDB-1999-GarofalakisRS #constraints #named #regular expression: SPIRIT: Sequential Pattern Mining with Regular Expression Constraints (MNG, RR, KS), pp. 223–234.
VLDB-1999-KoudasMJ #database: Mining Deviants in a Time Series Database (HVJ, NK, SM), pp. 102–113.
VLDB-1999-TamuraK #clustering #parallel: Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems (MT, MK), pp. 162–173.
ICEIS-1999-DuKM #algorithm #performance #reuse: Two Fast Algorithms for Repeated Mining of Association Rules Based on Ressource Reuse (XD, KK, AM), pp. 65–73.
ICEIS-1999-RamanA #algorithm: Candidate Drop Algorithm for Mining Association Rules (SR, TSA), pp. 132–139.
CIKM-1999-FengLYH #transaction: Mining Inter-Transaction Associations with Templates (LF, HL, JXY, JH), pp. 225–233.
CIKM-1999-HoltC #database #performance: Efficient Mining of Association Rules in Text Databases (JDH, SMC), pp. 234–242.
CIKM-1999-ParthasarathyZOD #incremental #interactive #sequence: Incremental and Interactive Sequence Mining (SP, MJZ, MO, SD), pp. 251–258.
KDD-1999-Agrawal #data mining: Data Mining: Crossing the Chasm (RA), p. 2.
KDD-1999-BayardoA: Mining the Most Interesting Rules (RJBJ, RA), pp. 145–154.
KDD-1999-BayP #category theory #data mining #detection #set: Detecting Change in Categorical Data: Mining Contrast Sets (SDB, MJP), pp. 302–306.
KDD-1999-BrinRS: Mining Optimized Gain Rules for Numeric Attributes (SB, RR, KS), pp. 135–144.
KDD-1999-BuntineFP #automation #data mining #source code #synthesis #towards: Towards Automated Synthesis of Data Mining Programs (WLB, BF, TP), pp. 372–376.
KDD-1999-ChengFZ #clustering: Entropy-based Subspace Clustering for Mining Numerical Data (CHC, AWCF, YZ), pp. 84–93.
KDD-1999-CortesP #agile #deployment #framework #platform: Information Mining Platforms: An Infrastructure for KDD Rapid Deployment (CC, DP), pp. 327–331.
KDD-1999-DongL #difference #performance #roadmap: Efficient Mining of Emerging Patterns: Discovering Trends and Differences (GD, JL), pp. 43–52.
KDD-1999-DorreGS: Text Mining: Finding Nuggets in Mountains of Textual Data (JD, PG, RS), pp. 398–401.
KDD-1999-HotzNPS #data mining #industrial: WAPS, a Data Mining Support Environment for the Planning of Warranty and Goodwill Costs in the Automobile Industry (EH, GN, BP, HS), pp. 417–419.
KDD-1999-LarsenA #clustering #documentation #effectiveness #linear #performance #using: Fast and Effective Text Mining Using Linear-Time Document Clustering (BL, CA), pp. 16–22.
KDD-1999-LeeSM #data flow #detection #experience #network: Mining in a Data-Flow Environment: Experience in Network Intrusion Detection (WL, SJS, KWM), pp. 114–124.
KDD-1999-LeshZO #classification #sequence: Mining Features for Sequence Classification (NL, MJZ, MO), pp. 342–346.
KDD-1999-LiuHM99a #multi: Mining Association Rules with Multiple Minimum Supports (BL, WH, YM), pp. 337–341.
KDD-1999-LiuHMC #using: Mining Interesting Knowledge Using DM-II (BL, WH, YM, SC), pp. 430–434.
KDD-1999-ManiDBD #data mining #modelling #statistics: Statistics and Data Mining Techniques for Lifetime Value Modeling (DRM, JD, AB, PD), pp. 94–103.
KDD-1999-MegalooikonomouDH #database #image: Mining Lesion-Deficit Associations in a Brain Image Database (VM, CD, EH), pp. 347–351.
KDD-1999-RogersLW #modelling: Mining GPS Data to Augment Road Models (SR, PL, CW), pp. 104–113.
KDD-1999-TungLHF #transaction: Breaking the Barrier of Transactions: Mining Inter-Transaction Association Rules (AKHT, HL, JH, LF), pp. 297–301.
KDD-1999-WangWLSSZ #algorithm #clustering #data mining: Evaluating a Class of Distance-Mapping Algorithms for Data Mining and Clustering (JTLW, XW, KIL, DS, BAS, KZ), pp. 307–311.
KDD-T-1999-Feldman #semistructured data: Mining Unstructured Data (RF), pp. 182–236.
KDD-T-1999-Holsheimer #data mining #process: Data Mining by Business Users: Integrating Data Mining in Business Processes (MH), pp. 266–291.
KDD-T-1999-RastogiS #algorithm #database #scalability: Scalable Algorithms for Mining Large Databases (RR, KS), pp. 73–140.
MLDM-1999-HongW #data mining #predict: Advanced in Predictive Data Mining Methods (SJH, SMW), pp. 13–20.
MLDM-1999-Sawaragi #data mining #effectiveness #interactive: Reproductive Process-Oriented Data Mining from Interactions between Human and Complex Artifact System (TS), pp. 180–194.
MLDM-1999-Scaringella #data mining #monitoring #risk management: A Data Mining Application for Monitoring Environmental Risks (AS), pp. 209–215.
SIGIR-1999-NieSID #automation #information retrieval #parallel #web: Cross-Language Information Retrieval Based on Parallel Texts and Automatic Mining of Parallel Texts from the Web (JYN, MS, PI, RD), pp. 74–81.
ASE-1999-Michail #data mining #library #reuse: Data Mining Library Reuse Patterns in User-Selected Applications (AM), p. 24–?.
ADL-1998-AhonenHKV #data mining #documentation: Applying Data Mining Techniques for Descriptive Phrase Extraction in Digital Document Collections (HA, OH, MK, AIV), pp. 2–11.
ADL-1998-FengF #algorithm: Binary Partition Based Algorithms for Mining Association Rules (JF, YF), pp. 30–34.
ADL-1998-ZaianeXH #data access #data mining #roadmap #web: Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs (ORZ, MX, JH), pp. 19–29.
SIGMOD-1998-AgrawalGGR #automation #clustering #data mining: Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications (RA, JG, DG, PR), pp. 94–105.
SIGMOD-1998-Bayardo #database: Efficiently Mining Long Patterns from Databases (RJBJ), pp. 85–93.
SIGMOD-1998-LiS #data mining #parallel: Free Parallel Data Mining (BL, DS), pp. 541–543.
SIGMOD-1998-NgLHP #optimisation: Exploratory Mining and Pruning Optimizations of Constrained Association Rules (RTN, LVSL, JH, AP), pp. 13–24.
SIGMOD-1998-NgLK #data mining: A Data Mining Application: Customes Retention at the Port of Singapore Authority (PSA) (KN, HL, HK), pp. 522–525.
SIGMOD-1998-SarawagiTA #database #relational: Integrating Mining with Relational Database Systems: Alternatives and Implications (SS, ST, RA), pp. 343–354.
SIGMOD-1998-ShintaniK #algorithm #classification #parallel: Parallel Mining Algorithms for Generalized Association Rules with Classification Hierarchy (TS, MK), pp. 25–36.
SIGMOD-1998-TsurUACMNR #query: Query Flocks: A Generalization of Association-Rule Mining (ST, JDU, SA, CC, RM, SN, AR), pp. 1–12.
SIGMOD-1998-ZaianeHLCC #data mining #multi #named #prototype: MultiMediaMiner: A System Prototype for Multimedia Data Mining (ORZ, JH, ZNL, SHSC, JC), pp. 581–583.
VLDB-1998-ChakrabartiSD #using: Mining Surprising Patterns Using Temporal Description Length (SC, SS, BD), pp. 606–617.
VLDB-1998-EsterKSWX #clustering #incremental: Incremental Clustering for Mining in a Data Warehousing Environment (ME, HPK, JS, MW, XX), pp. 323–333.
VLDB-1998-George #data mining #named #parallel: DMS: A Parallel Data Mining Server (FAWG), p. 702.
VLDB-1998-KnorrN #algorithm #dataset #scalability: Algorithms for Mining Distance-Based Outliers in Large Datasets (EMK, RTN), pp. 392–403.
VLDB-1998-KornLKF #data mining #paradigm #performance: Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining (FK, AL, YK, CF), pp. 582–593.
VLDB-1998-MorimotoFMTY #algorithm #category theory #database: Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases (YM, TF, HM, TT, KY), pp. 380–391.
VLDB-1998-RiedelGF #data mining #multi #scalability: Active Storage for Large-Scale Data Mining and Multimedia (ER, GAG, CF), pp. 62–73.
VLDB-1998-SilversteinBMU #scalability: Scalable Techniques for Mining Causal Structures (CS, SB, RM, JDU), pp. 594–605.
ICSM-1998-OcaC #data mining #identification #using: Identification of Data Cohesive Subsystems Using Data Mining Techniques (CMdO, DLC), pp. 16–23.
WCRE-1998-Dayani-FardJ #repository #reverse engineering: Reverse Engineering by Mining Dynamic Repositories (HDF, IJ), pp. 174–182.
CIKM-1998-HaradaAOT #parallel: Dynamic Skew Handling in Parallel Mining of Association Rules (LH, NA, KO, RT), pp. 76–85.
CIKM-1998-LiYC #abstraction #database #framework #multi #named #sequence: MALM: A Framework for Mining Sequence Database at Multiple Abstraction Levels (CSL, PSY, VC), pp. 267–272.
CIKM-1998-TungTL #named #online #optimisation #using: BROOM: Buffer Replacement using Online Optimization by Mining (AKHT, YCT, HL), pp. 185–192.
KDD-1998-BerchtoldJR #data mining #diagrams #independence #visual notation: Independence Diagrams: A Technique for Visual Data Mining (SB, HVJ, KAR), pp. 139–143.
KDD-1998-BorgesL #database #hypermedia: Mining Association Rules in Hypertext Databases (JB, ML), pp. 149–153.
KDD-1998-FeeldersCM #bias: Mining in the Presence of Selectivity Bias and its Application to Reject Inference (AJF, SC, GJM), pp. 199–203.
KDD-1998-GrecuB #data mining #distributed #learning: Coactive Learning for Distributed Data Mining (DLG, LAB), pp. 209–213.
KDD-1998-GuralnikWS #sequence: Pattern Directed Mining of Sequence Data (VG, DW, JS), pp. 51–57.
KDD-1998-HanGY #database: Mining Segment-Wise Periodic Patterns in Time-Related Databases (JH, WG, YY), pp. 214–218.
KDD-1998-KellyHA #data mining #performance: Defining the Goals to Optimise Data Mining Performance (MGK, DJH, NMA), pp. 234–238.
KDD-1998-LeeSM #detection #modelling: Mining Audit Data to Build Intrusion Detection Models (WL, SJS, KWM), pp. 66–72.
KDD-1998-LingL #data mining #problem: Data Mining for Direct Marketing: Problems and Solutions (CXL, CL), pp. 73–79.
KDD-1998-LiuHM #classification: Integrating Classification and Association Rule Mining (BL, WH, YM), pp. 80–86.
KDD-1998-NakhaeizadehS #algorithm #data mining #evaluation #personalisation #towards: Towards the Personalization of Algorithms Evaluation in Data Mining (GN, AS), pp. 289–293.
KDD-1998-ParthasarathyZL #memory management #parallel: Memory Placement Techniques for Parallel Association Mining (SP, MJZ, WL), pp. 304–308.
KDD-1998-PinheiroS #database #semistructured data: Methods for Linking and Mining Massive Heterogeneous Databases (JCP, DXS), pp. 309–313.
KDD-1998-SinghCHSA #architecture #robust: A Robust System Architecture for Mining Semi-Structured Data (LS, BC, RH, PS, KA), pp. 329–333.
KDD-1998-StaudtKR #data mining: A Data Mining Support Environment and its Application on Insurance Data (MS, JUK, UR), pp. 105–111.
KDD-1998-Stolfo #classification #database: Mining Databases with Different Schemas: Integrating Incompatible Classifiers (ALP, SJS), pp. 314–318.
KDD-1998-Subramonian #data mining: Defining diff as a Data Mining Primitive (RS), pp. 334–338.
KDD-1998-ThomasS #query #sql #using: Mining Generalized Association Rules and Sequential Patterns Using SQL Queries (ST, SS), pp. 344–348.
KDD-1998-ZakiLO #named #sequence: PlanMine: Sequence Mining for Plan Failures (MJZ, NL, MO), pp. 369–374.
SIGIR-1998-LinSCHKH #approach #classification #documentation #internet #semantics: Extracting Classification Knowledge of Internet Documents with Mining Term Associations: A Semantic Approach (SHL, CSS, MCC, JMH, MTK, YMH), pp. 241–249.
TOOLS-ASIA-1998-WangH #data mining #implementation #research: The Research and Implementation of Data Warehouse and Data Mining in Decision Support System (BW, JH), pp. 362–371.
SAC-1998-MachucaM #data mining #database #precise #relational #set: Enhancing the exploitation of data mining in relational database systems via the rough sets theory including precision variables (FM, MM), pp. 70–73.
HPDC-1998-OguchiSTK #clustering #data mining #effectiveness #evaluation #optimisation #parallel #parametricity #protocol #scalability: Optimizing Protocol Parameters to Large Scale PC Cluster and Evaluation of its Effectiveness with Parallel Data Mining (MO, TS, TT, MK), pp. 34–41.
PODS-1997-GunopulosKMT #data mining #machine learning: Data mining, Hypergraph Transversals, and Machine Learning (DG, RK, HM, HT), pp. 209–216.
SIGMOD-1997-HanKK #data mining #parallel #scalability: Scalable Parallel Data Mining for Association Rules (EHH, GK, VK), pp. 277–288.
SIGMOD-1997-HanKS #data mining #named #prototype: GeoMiner: A System Prototype for Spatial Data Mining (JH, KK, NS), pp. 553–556.
VLDB-1997-KietzRS: Mining Insurance Data at Swiss Life (JUK, UR, MS), pp. 562–566.
VLDB-1997-ShaferA #algorithm #data mining #parallel #similarity: Parallel Algorithms for High-dimensional Similarity Joins for Data Mining Applications (JCS, RA), pp. 176–185.
VLDB-1997-WangYM #approach #data mining #grid #named #statistics: STING: A Statistical Information Grid Approach to Spatial Data Mining (WW, JY, RRM), pp. 186–195.
CIKM-1997-ChanA #fuzzy: Mining Fuzzy Association Rules (KCCC, WHA), pp. 209–215.
CIKM-1997-HahnS: Knowledge Mining from Textual Sources (UH, KS), pp. 83–90.
CIKM-1997-ParkYC: Mining Association Rules with Adjustable Accuracy (JSP, PSY, MSC), pp. 151–160.
CIKM-1997-YoonSP #data mining #query #using: Intensional Query Processing Using Data Mining Approaches (SCY, IYS, EKP), pp. 201–208.
KDD-1997-AronisP #algorithm #data mining #performance: Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation (JMA, FJP), pp. 119–122.
KDD-1997-Bayardo #classification: Brute-Force Mining of High-Confidence Classification Rules (RJBJ), pp. 123–126.
KDD-1997-BergstenSS #analysis #data mining #machine learning: Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis (UB, JS, PS), pp. 127–130.
KDD-1997-BrunkKK #data mining #named: MineSet: An Integrated System for Data Mining (CB, JK, RK), pp. 135–138.
KDD-1997-ChattratichatDGGHKSTY #challenge #data mining #scalability: Large Scale Data Mining: Challenges and Responses (JC, JD, MG, YG, HH, MK, JS, HWT, DY), pp. 143–146.
KDD-1997-DeCoste #behaviour #multi: Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes (DD), pp. 151–154.
KDD-1997-EngelsLS #data mining: A Guided Tour through the Data Mining Jungle (RE, GL, RS), pp. 163–166.
KDD-1997-FeldmanAAZK #documentation #keyword: Maximal Association Rules: A New Tool for Mining for Keyword Co-Occurrences in Document Collections (RF, YA, AA, AZ, WK), pp. 167–170.
KDD-1997-FeldmanKZ #data mining #documentation #visualisation: Visualization Techniques to Explore Data Mining Results for Document Collections (RF, WK, AZ), pp. 16–23.
KDD-1997-HaimowitzGS #database #distributed: Integrating and Mining Distributed Customer Databases (IJH, ÖGA, HS), pp. 179–182.
KDD-1997-HinkeRRG #independence #roadmap: Target-Independent Mining for Scientific Data: Capturing Transients and Trends for Phenomena Mining (THH, JAR, HSR, SJG), pp. 187–190.
KDD-1997-KahngM #algorithm: Mining Generalized Term Associations: Count Propagation Algorithm (JK, WHKL, DM), pp. 203–206.
KDD-1997-KamberHC #multi #using: Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes (MK, JH, JC), pp. 207–210.
KDD-1997-KarguptaHS #architecture #data mining #distributed #scalability: Scalable, Distributed Data Mining — An Agent Architecture (HK, IH, BS), pp. 211–214.
KDD-1997-KramerPH #machine learning: Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail (SK, BP, CH), pp. 223–226.
KDD-1997-MihalisinT #data mining #performance #robust #visual notation: Fast Robust Visual Data Mining (TM, JT), pp. 231–234.
KDD-1997-NakhaeizadehS #algorithm #data mining #development #evaluation #metric #multi: Development of Multi-Criteria Metrics for Evaluation of Data Mining Algorithms (GN, AS), pp. 37–42.
KDD-1997-SrikantVA #constraints: Mining Association Rules with Item Constraints (RS, QV, RA), pp. 67–73.
KDD-1997-ZupanBBC #approach #composition #data mining #dataset: A Dataset Decomposition Approach to Data Mining and Machine Discovery (BZ, MB, IB, BC), pp. 299–302.
TOOLS-ASIA-1997-Dai #approach #data mining #database #integration #multi #object-oriented: An Object-Oriented Approach to Schema Integration and Data Mining in Multiple Databases (HD), pp. 294–303.
SAC-1997-ChanA #algorithm #effectiveness: An effective algorithm for mining interesting quantitative association rules (KCCC, WHA), pp. 88–90.
SAC-1997-GoliP #data mining #multi: Application of domain vector perfect hash join for multimedia data mining (VNRG, WP), pp. 334–339.
SAC-1997-Mazlack #database: Developing a focus in unsupervised database mining (LJM), pp. 187–191.
ILPS-1997-Mannila #data mining #database #induction: Inductive Databases and Condensed Representations for Data Mining (HM), pp. 21–30.
PODS-1996-BettiniWJ #data mining #multi #testing: Testing Complex Temporal Relationships Involving Multiple Granularities and Its Application to Data Mining (CB, XSW, SJ), pp. 68–78.
PODS-1996-FukudaMMT: Mining Optimized Association Rules for Numeric Attributes (TF, YM, SM, TT), pp. 182–191.
SIGMOD-1996-FukudaMMT #2d #algorithm #data mining #using #visualisation: Data Mining Using Two-Dimensional Optimized Accociation Rules: Scheme, Algorithms, and Visualization (TF, YM, SM, TT), pp. 13–23.
SIGMOD-1996-Han #data mining: Data Mining Techniques (JH), p. 545.
SIGMOD-1996-HanFWCZK #database #interactive #multi #named #relational: DBMiner: Interactive Mining of Multiple-Level Knowledge in Relational Databases (JH, YF, WW, JC, ORZ, KK), p. 550.
SIGMOD-1996-SrikantA #relational #scalability: Mining Quantitative Association Rules in Large Relational Tables (RS, RA), pp. 1–12.
VLDB-1996-MeoPC: A New SQL-like Operator for Mining Association Rules (RM, GP, SC), pp. 122–133.
VLDB-1996-MiningGroup #data mining #visualisation: MineSet(tm): A System for High-End Data Mining and Visualization, p. 595.
VLDB-1996-ShaferAM #classification #data mining #named #parallel #scalability: SPRINT: A Scalable Parallel Classifier for Data Mining (JCS, RA, MM), pp. 544–555.
VLDB-1996-ViverosNR #data mining #health #information management: Applying Data Mining Techniques to a Health Insurance Information System (MSV, JPN, MJR), pp. 286–294.
AKDDM-1996-FayyadPS #data mining #information management #overview #perspective: From Data Mining to Knowledge Discovery: An Overview (UMF, GPS, PS), pp. 1–34.
AKDDM-1996-HanF #data mining #induction: Attribute-Oriented Induction in data Mining (JH, YF), pp. 399–421.
AKDDM-1996-Piatetsky-Shapiro #data mining #information management #internet: Data Mining and Knowledge Discovery Internet Resources (GPS), pp. 593–595.
AKDDM-1996-ShenOMZ #data mining: Metaqueries for Data Mining (WMS, KO, BGM, CZ), pp. 375–398.
AKDDM-1996-SimoudisLK #data mining #deduction #induction #reasoning: Integrating Inductive and Deductive Reasoning for Data Mining (ES, BL, RK), pp. 353–373.
AKDDM-1996-Uthurusamy #challenge #data mining #information management: From Data Mining to Knowledge Discovery: Current Challenges and Future Directions (RU), pp. 561–569.
CIKM-1996-FortinL #approach #multi #object-oriented: An Object-Oriented Approach to Multi-Level Association Rule Mining (SF, LL), pp. 65–72.
CIKM-1996-HanP #algorithm: Background for Association Rules and Cost Estimate of Selected Mining Algorithms (JLH, AWP), pp. 73–80.
ICML-1996-Mannila #data mining #machine learning: Data Mining and Machine Learning (HM), p. 555.
KDD-1996-AgrawalMSSAB #data mining: The Quest Data Mining System (RA, MM, JCS, RS, AA, TB), pp. 244–249.
KDD-1996-AgrawalS #data mining #database #relational: Developing Tightly-Coupled Data Mining Applications on a Relational Database System (RA, KS), pp. 287–290.
KDD-1996-CiesielskiP #database #hybrid #overview #using: Using a Hybrid Neural/Expert System for Data Base Mining in Market Survey Data (VC, GP), pp. 38–43.
KDD-1996-Czyzewski: Mining Knowledge in Noisy Audio Data (AC), pp. 220–225.
KDD-1996-Fahner #data mining #interactive: Data Mining with Sparse and Simplified Interaction Selection (GF), pp. 359–362.
KDD-1996-FawcettP #data mining #effectiveness #machine learning #profiling: Combining Data Mining and Machine Learning for Effective User Profiling (TF, FJP), pp. 8–13.
KDD-1996-FayyadPS #data mining #framework #information management #towards: Knowledge Discovery and Data Mining: Towards a Unifying Framework (UMF, GPS, PS), pp. 82–88.
KDD-1996-FeldmanH: Mining Associations in Text in the Presence of Background Knowledge (RF, HH), pp. 343–346.
KDD-1996-FlockhartR #approach #data mining #search-based: A Genetic Algorithm-Based Approach to Data Mining (IWF, NJR), pp. 299–302.
KDD-1996-FultonKSW #data mining #induction #interactive #towards: Local Induction of Decision Trees: Towards Interactive Data Mining (TF, SK, SS, DLW), pp. 14–19.
KDD-1996-GaneshSR #database #identification #integration: Mining Entity-Identification Rules for Database Integration (MG, JS, TR), pp. 291–294.
KDD-1996-GrossmanBNP #data mining #optimisation: Data Mining and Tree-Based Optimization (RLG, HB, DN, HVP), pp. 323–326.
KDD-1996-HanFWCGKLLRSXZ #database #named #relational #scalability: DBMiner: A System for Mining Knowledge in Large Relational Databases (JH, YF, WW, JC, WG, KK, DL, YL, AR, NS, BX, ORZ), pp. 250–255.
KDD-1996-ImielinskiVA #database #interface #named #programming #query: DataMine: Application Programming Interface and Query Language for Database Mining (TI, AV, AA), pp. 256–262.
KDD-1996-JohnL #data mining: Static Versus Dynamic Sampling for Data Mining (GHJ, PL), pp. 367–370.
KDD-1996-KontkanenMT #data mining #finite #predict: Predictive Data Mining with Finite Mixtures (PK, PM, HT), pp. 176–182.
KDD-1996-Piatetsky-ShapiroBKKS #data mining #industrial #information management #overview: An Overview of Issues in Developing Industrial Data Mining and Knowledge Discovery Applications (GPS, RJB, TK, WK, ES), pp. 89–95.
KDD-1996-ProvanS #case study #data mining: Data Mining and Model Simplicity: A Case Study in Diagnosis (GMP, MS), pp. 57–62.
KDD-1996-ShekMMN #data mining #distributed #scalability: Scalable Exploratory Data Mining of Distributed Geoscientific Data (ECS, RRM, EM, KWN), pp. 32–37.
KDD-1996-ShenL #data mining #generative: Metapattern Generation for Integrated Data Mining (WMS, BL), pp. 152–157.
KDD-1996-StolorzD #data mining #detection #named #scalability: Quakefinder: A Scalable Data Mining System for Detecting Earthquakes from Space (PES, CD), pp. 208–213.
KDD-1996-WrobelWSE #data mining: Extensibility in Data Mining Systems (SW, DW, ES, WE), pp. 214–219.
KDD-1996-ZytkowZ #automation: Automated Pattern Mining with a Scale Dimension (JMZ, RZ), pp. 158–163.
SEKE-1996-ChangW #case study #data mining: Scientific Data Mining: A Case Study (CYC, JTLW), pp. 100–107.
SIGMOD-1995-ParkCY #algorithm #effectiveness: An Effective Hash Based Algorithm for Mining Association Rules (JSP, MSC, PSY), pp. 175–186.
VLDB-1995-LuSL #approach #data mining #named: NeuroRule: A Connectionist Approach to Data Mining (HL, RS, HL), pp. 478–489.
VLDB-1995-SavasereON #algorithm #database #performance #scalability: An Efficient Algorithm for Mining Association Rules in Large Databases (AS, EO, SBN), pp. 432–444.
VLDB-1995-SrikantA: Mining Generalized Association Rules (RS, RA), pp. 407–419.
CIKM-1995-AnandBH #data mining: The Role of Domain Knowledge in Data Mining (SSA, DAB, JGH), pp. 37–43.
CIKM-1995-Han #concept #multi: Mining Knowledge at Multiple Concept Levels (JH), pp. 19–24.
CIKM-1995-ParkCY #data mining #parallel #performance: Efficient Parallel and Data Mining for Association Rules (JSP, MSC, PSY), pp. 31–36.
KDD-1995-AgrawalP #data mining: Active Data Mining (RA, GP), pp. 3–8.
KDD-1995-DaoP #integration: Applying a Data Miner To Heterogeneous Schema Integration (SD, BP), pp. 63–68.
KDD-1995-FeeldersLZ #case study #data mining #evaluation: Data Mining for Loan Evaluation at ABN AMRO: A Case Study (AJF, AJFlL, JWvZ), pp. 106–111.
KDD-1995-HolsheimerKMT #data mining #database: A Perspective on Databases and Data Mining (MH, MLK, HM, HT), pp. 150–155.
KDD-1995-SeshadriSW #data mining #feature model: Feature Extraction for Massive Data Mining (VS, RS, SMW), pp. 258–262.
KDD-1995-StolorzNMMSSYNCMF #data mining #dataset #performance #scalability: Fast Spatio-Temporal Data Mining of Large Geophysical Datasets (PES, HN, EM, RRM, ECS, JRS, JY, KWN, SYC, CRM, JDF), pp. 300–305.
PODS-1994-Agrawal #database #tutorial: Tutorial Database Mining (RA), pp. 75–76.
SIGMOD-1994-AgrawalCFGHIIMMSS #database #named: Quest: A Project on Database Mining (RA, MJC, CF, SPG, MAWH, TI, BRI, AM, HM, RS, ANS), p. 514.
VLDB-1994-AgrawalS #algorithm #database #performance #scalability: Fast Algorithms for Mining Association Rules in Large Databases (RA, RS), pp. 487–499.
VLDB-1994-NgH #clustering #data mining #effectiveness #performance: Efficient and Effective Clustering Methods for Spatial Data Mining (RTN, JH), pp. 144–155.
KDD-1994-AnandBH #architecture #database #optimisation #preprocessor #query #semantics: Database Mining in the Architecture of a Semantic Preprocessor for State Aware Query Optimization (SSA, DAB, JGH), pp. 287–298.
KDD-1994-HolsheimerK #architecture #data mining: Architectural Support for Data Mining (MH, MLK), pp. 217–228.
KDD-1994-SimoudisLK #database #deduction #induction #reasoning: Integrating Inductive and Deductive Reasoning for Database Mining (ES, BL, RK), pp. 37–48.
SIGMOD-1993-AgrawalIS #database #scalability #set: Mining Association Rules between Sets of Items in Large Databases (RA, TI, ANS), pp. 207–216.
HCI-ACS-1993-KeranRS #automation #mobile #perspective: Automation of Mobile Equipment in Mining: A Human Factors Perspective (CMK, RFR, TJS), pp. 307–312.
HCI-ACS-1993-NtuenPK #architecture #human-computer #interface: A Blackboard Architecture for Human-Machine Interface in a Mining Teleoperation (CAN, EHP, SMK), pp. 50–55.
CIKM-1993-CrompC #data mining #image #multi: Data Mining of Multi-dimensional Remotely Sensed Images (RFC, WJC), pp. 471–480.
ICML-1993-RaoVF #data mining: Data Mining of Subjective Agricultural Data (RBR, TBV, TWF), pp. 244–251.
VLDB-1992-AgrawalGIIS #classification #database: An Interval Classifier for Database Mining Applications (RA, SPG, TI, BRI, ANS), pp. 560–573.
KDD-1991-KaufmanMK #database: Mining for Knowledge in Databases: Goals and General Description of the INLEN System (KAK, RSM, LK), pp. 449–464.
KDD-1991-ZytkowB #database #interactive: Interactive Mining of Regularities in Databases (JMZ, JB), pp. 31–54.