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Tag #data mining

475 papers:

EDMEDM-2019-YahyaMO #education #effectiveness #mining #novel #source code #using
A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs (AAY, FAM, AO).
KDDKDD-2019-Chen0 #machine learning #mining #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.
KDDKDD-2019-LiX #mining #named #privacy #scalability
PrivPy: General and Scalable Privacy-Preserving Data Mining (YL, WX), pp. 1299–1307.
KDDKDD-2019-VreekenY #mining #theory and practice
Modern MDL meets Data Mining Insights, Theory, and Practice (JV, KY), pp. 3229–3230.
KDDKDD-2019-XiaoS #development #mining #named #tutorial
Tutorial: Data Mining Methods for Drug Discovery and Development (CX, JS), pp. 3195–3196.
CASECASE-2019-Dagnino #mining #process
Data Mining Methods to Analyze Alarm Logs in IoT Process Control Systems (AD), pp. 323–330.
EDMEDM-2018-ChenLG #education #mining #online
Re-designing the Structure of Online Courses to Empower Educational Data Mining (ZC, SL, GG).
CIKMCIKM-2018-WangYWJZZW #graph #mining #named #scalability
AceKG: A Large-scale Knowledge Graph for Academic Data Mining (RW, YY, JW, YJ, YZ, WZ0, XW), pp. 1487–1490.
JCDLJCDL-2017-SaggionR #mining
Scholarly Data Mining: Making Sense of Scientific Literature (HS, FR), pp. 346–347.
EDMEDM-2017-BeckCB #education #learning #mining
Workshop proposal: deep learning for educational data mining (JB, MC, RSB).
EDMEDM-2017-LynchBXG #education #graph #mining
Graph-based Educational Data Mining (CL, TB, LX, NG).
CIKMCIKM-2017-HuJ #mining #modelling
IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models (XH, SJ), pp. 2565–2566.
KDDKDD-2017-BlalockG #mining #named #performance
Bolt: Accelerated Data Mining with Fast Vector Compression (DWB, JVG), pp. 727–735.
KDDKDD-2017-GanH #framework #mining #scalability
A Data Mining Framework for Valuing Large Portfolios of Variable Annuities (GG, JXH), pp. 1467–1475.
CASECASE-2017-LuLXZB #industrial #mining #process #research
Research on data mining service and its application case in complex industrial process (QL, ZJL, QX, YZ, JB), pp. 1124–1129.
EDMEDM-2016-HaoLDKK #analysis #collaboration #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.
EDMEDM-2016-Penteado #assessment #estimation #mining #scalability #semantics #using
Estimation of prerequisite skills model from large scale assessment data using semantic data mining (BEP), pp. 675–677.
EDMEDM-2016-SabourinMW #education #mining #tool support
SAS Tools for Educational Data Mining (JS, SWM, ADW), pp. 632–633.
EDMEDM-2016-Sherzad #challenge #education #mining
Applicability of Educational Data Mining in Afghanistan: Opportunities and Challenges (ARS), pp. 634–635.
CHI-PLAYCHI-PLAY-2016-WellsCLMGS #mining #network
Mining for Gold (and Platinum): PlayStation Network Data Mining (LW, AJCS, IJL, LM, BG, KdS), pp. 304–312.
CIKMCIKM-2016-AgrawalC #mining #predict #using
A Fatigue Strength Predictor for Steels Using Ensemble Data Mining: Steel Fatigue Strength Predictor (AA, ANC), pp. 2497–2500.
CIKMCIKM-2016-ChenDWST #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.
CIKMCIKM-2016-ShiTWA #big 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.
KDDKDD-2016-HajianBC #algorithm #bias #mining
Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining (SH, FB, CC0), pp. 2125–2126.
KDDKDD-2016-PrakashR #algorithm #mining #modelling
Leveraging Propagation for Data Mining: Models, Algorithms and Applications (BAP, NR), pp. 2133–2134.
KDDKDD-2016-WangZD #matrix #mining #modelling
Healthcare Data Mining with Matrix Models (FW0, PZ0, JD), pp. 2137–2138.
CASECASE-2016-ChengZWCJL #case study #energy #fault #mining #using
Case studies of fault diagnosis and energy saving in buildings using data mining techniques (ZC, QZ, FW, ZC, YJ, YL), pp. 646–651.
EDMEDM-2015-BravoRLP #education #mining #online #tool support
Exploring the Influence of ICT in online Education Through Data Mining Tools (JB, SJR, JML, SP), pp. 540–543.
EDMEDM-2015-CrossleyMBWPBB #education #mining #online
Language to Completion: Success in an Educational Data Mining Massive Open Online Class (SAC, DSM, RSB, YW, LP, TB, YB), pp. 388–391.
EDMEDM-2015-CuadrosGRGZO #education #mining
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.
EDMEDM-2015-SabourinKFM #education #industrial #mining #privacy #student
Student Privacy and Educational Data Mining: Perspectives from Industry (JS, LK, CF, SWM), pp. 164–170.
EDMEDM-2015-Tibbles #learning #mining
Exploring the Impact of Spacing in Mathematics Learning through Data Mining (RT), pp. 590–591.
ICEISICEIS-v1-2015-Castanon-PugaSG #algorithm #fuzzy #logic #mining #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.
KDDKDD-2015-ArlorioCLLP #assessment #authentication #mining
Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont (MA, JDC, GL, ML, LP), pp. 1671–1680.
KDDKDD-2015-WickerKDSBKW0 #mining #smell
Cinema Data Mining: The Smell of Fear (JW, NK, BD, CS, EB, TK, JW, SK), pp. 1295–1304.
MLDMMLDM-2015-MoldovanM #learning #mining #performance #using
Learning the Relationship Between Corporate Governance and Company Performance Using Data Mining (DM, SM), pp. 368–381.
CASECASE-2015-NouaouriSA #mining #predict #problem
Evidential data mining for length of stay (LOS) prediction problem (IN, AS, HA), pp. 1415–1420.
DATEDATE-2015-FarkashHS #debugging #locality #mining
Data mining diagnostics and bug MRIs for HW bug localization (MF, BGH, BS), pp. 79–84.
PDPPDP-2015-AltomareCT #energy #migration #mining #modelling #predict #virtual machine
Energy-Aware Migration of Virtual Machines Driven by Predictive Data Mining Models (AA, EC, DT), pp. 549–553.
ICLPICLP-2015-Hallen #higher-order #logic #mining #specification
Higher Order Support in Logic Specification Languages for Data Mining Applications (MvdH), pp. 330–336.
EDMEDM-2014-CrossleyKVM #assessment #mining
The Importance of Grammar and Mechanics in Writing Assessment and Instruction: Evidence from Data Mining (SAC, KK, LKV, DSM), pp. 300–303.
EDMEDM-2014-FuentesRGV #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.
EDMEDM-2014-MartinVAMJ #design #education #mining #research
Microgenetic Designs for Educational Data Mining Research: Poster (TM, NFV, AA, JM, PJ), pp. 387–388.
EDMEDM-2014-MorrisonNSDKR #database #mining
Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data Mining (DMM, BN, BS, VVD, CK, VR), pp. 335–336.
EDMEDM-2014-RayBR #mining #using
Using Data Mining to Automate ADDIE (FR, KWB, RR), pp. 429–430.
EDMEDM-2014-ShuQF #education #experience #learning #mining #student
Educational Data Mining and Analyzing of Student Learning Outcomes from the Perspective of Learning Experience (ZS, QFQ, LQF), pp. 359–360.
EDMEDM-2014-SyedJG #mining
Data mining of undergraduate course evaluations (SJS, YHJ, LG), pp. 347–348.
ICSMEICSME-2014-ZhouTGG #classification #debugging #mining
Combining Text Mining and Data Mining for Bug Report Classification (YZ, YT, RG, HCG), pp. 311–320.
CoGCIG-2014-GalliLL #design pattern #mining
Applying data mining to extract design patterns from Unreal Tournament levels (LG, PLL, DL), pp. 1–8.
HCIHCI-AS-2014-Hussain #mining
Getting the Most from CRM Systems: Data Mining in SugarCRM, Finding Important Patterns (QH), pp. 693–699.
ICEISICEIS-v1-2014-AmaralCRGTS #approach #framework #image #mining
The SITSMining Framework — A Data Mining Approach for Satellite Image Time Series (BFA, DYTC, LASR, RRdVG, AJMT, EPMdS), pp. 225–232.
ICEISICEIS-v1-2014-AntunesS #mining #roadmap
New Trends in Knowledge Driven Data Mining (CA, AS), pp. 346–351.
ICEISICEIS-v1-2014-DominguezAERLE #fuzzy #logic #mining #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.
ICEISICEIS-v1-2014-GuerineRP #metaheuristic #mining
Extending the Hybridization of Metaheuristics with Data Mining to a Broader Domain (MG, IR, AP), pp. 395–406.
KDDKDD-2014-Etzioni #future of #mining
The battle for the future of data mining (OE), p. 1.
KDDKDD-2014-XuWCGSKDL #delivery #mining #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.
KDDKDD-2014-ZhengZLJXLSZLTLDLW #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.
KDIRKDIR-2014-KurasEAH #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.
KDIRKDIR-2014-MorenoGV #mining #recognition #using #word
Violence Recognition in Spanish Words using Data Mining (AFM, SBGB, JGVR), pp. 210–216.
KEODKEOD-2014-Talia #big data #distributed #information management #mining
Big Data Mining Services and Distributed Knowledge Discovery Applications on Clouds (DT), pp. 1–5.
KMISKMIS-2014-VelosoPSSRA0 #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.
MLDMMLDM-2014-KuleshovB #learning #mining
Manifold Learning in Data Mining Tasks (APK, AVB), pp. 119–133.
MLDMMLDM-2014-WangLK #concurrent #mining
Applications of Concurrent Sequential Patterns in Protein Data Mining (CW, JL, MK), pp. 243–257.
RecSysRecSys-2014-JannachF #mining #modelling #process #recommendation
Recommendation-based modeling support for data mining processes (DJ, SF), pp. 337–340.
CASECASE-2014-HungCYDYW #behaviour #mining
Data mining for analysing kiosk usage behavior patterns (YSH, KLBC, CTY, GFD, YHY, NCW), pp. 1115–1120.
DACDAC-2014-LinWC #design #logic #mining #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.
DACDAC-2014-WangA #constraints #mining
Data Mining In EDA — Basic Principles, Promises, and Constraints (LCW, MSA), p. 6.
DATEDATE-2014-LagraaTP #mining #scalability #simulation #using
Scalability bottlenecks discovery in MPSoC platforms using data mining on simulation traces (SL, AT, FP), pp. 1–6.
SIGMODSIGMOD-2013-AchtertKSZ #3d #coordination #interactive #mining
Interactive data mining with 3D-parallel-coordinate-trees (EA, HPK, ES, AZ), pp. 1009–1012.
SIGMODSIGMOD-2013-OrdonezGGCBQ #algorithm #as a service #database #in the cloud #mining #relational
Data mining algorithms as a service in the cloud exploiting relational database systems (CO, JGG, CGA, WC, VB, MSQ), pp. 1001–1004.
ITiCSEITiCSE-2013-MedinaPGR #education #learning #mining #programming #using
Assistance in computer programming learning using educational data mining and learning analytics (CFM, JRPP, VMÁG, MdPPR), pp. 237–242.
CoGCIG-2013-ChoK #comparison #mining
Comparison of human and AI bots in StarCraft with replay data mining (HCC, KJK), pp. 1–2.
ICEISICEIS-v1-2013-al-KetbiC #integration #mining
Integration of Decision Support Systems and Data Mining for Improved Decision Making (OaK, MC), pp. 482–489.
CIKMCIKM-2013-Giles #big data #information management #mining
Scholarly big data: information extraction and data mining (CLG), pp. 1–2.
KDDKDD-2013-EmersonWN #mining #profiling
A data mining driven risk profiling method for road asset management (DE, JW, RN), pp. 1267–1275.
KDDKDD-2013-WangDYWCSI #clustering #framework #identification #mining #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.
KDDKDD-2013-ZengJZLLLSZLDLW #distributed #mining #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.
KDIRKDIR-KMIS-2013-PereiraRT #mining #source code #student
Extraction Student Dropout Patterns with Data Mining Techniques in Undergraduate Programs (RTP, ACR, JJT), pp. 136–142.
MLDMMLDM-2013-GaoD #distributed #mining #performance #using
Improving the Efficiency of Distributed Data Mining Using an Adjustment Work Flow (JG, JD), pp. 69–83.
MLDMMLDM-2013-ValencioKMSM #3d #mining #visualisation
3D Geovisualisation Techniques Applied in Spatial Data Mining (CRV, TK, CAdM, RCGdS, JMM), pp. 57–68.
DATEDATE-2013-LagraaTP #concurrent #data access #identification #memory management #mining #simulation
Data mining MPSoC simulation traces to identify concurrent memory access patterns (SL, AT, FP), pp. 755–760.
WCREWCRE-2012-ZiftciK #feature model #mining #using
Feature Location Using Data Mining on Existing Test-Cases (CZ, IK), pp. 155–164.
ICEISICEIS-v2-2012-LukaszewskiJL #mining #ontology #semantics #using
Attribute Value Ontology — Using Semantics in Data Mining (TL, JJ, AL), pp. 329–334.
KDDKDD-2012-Holmes #mining
Developing data mining applications (GH), p. 225.
KDDKDD-2012-Lin #case study #experience #machine learning #mining
Experiences and lessons in developing industry-strength machine learning and data mining software (CJL), p. 1176.
KDDKDD-2012-MaoCCLKB #approach #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.
KDDKDD-2012-YuZSWWQZ #analysis #in the cloud #mining #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.
KDIRKDIR-2012-BhattacharjeeBG #mining #network #optimisation #using
Product Assortment Decisions for a Network of Retail Stores using Data Mining with Optimization (SB, FB, RDG), pp. 319–323.
KEODKEOD-2012-KhairMZ #education #mining #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.
KMISKMIS-2012-PortelaPS #mining #modelling #pervasive #predict
Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine (FP, FP, MFS), pp. 81–88.
CASECASE-2012-HoSY #mining #modelling
Data Mining of Life Log for Developing a User model-based Service Application (YH, ESS, TY), pp. 757–760.
ICLPICLP-2012-BlockeelBBCP #machine learning #mining #modelling #problem
Modeling Machine Learning and Data Mining Problems with FO(·) (HB, BB, MB, BdC, SDP, MD, AL, JR, SV), pp. 14–25.
SIGMODSIGMOD-2011-OrdonezP #algorithm #mining
One-pass data mining algorithms in a DBMS with UDFs (CO, SKP), pp. 1217–1220.
VLDBVLDB-2011-JinLLH #detection #named #network #social #social media
SocialSpamGuard: A Data Mining-Based Spam Detection System for Social Media Networks (XJ, CXL, JL, JH), pp. 1458–1461.
MSRMSR-2011-Whitehead #game studies #mining #what
Fantasy, farms, and freemium: what game data mining teaches us about retention, conversion, and virality (JW), p. 1.
CoGCIG-2011-AsheSK #machine learning #mining #named
Keynotes: Data mining and machine learning applications in MMOs (GA, NRS, JHK).
ICEISICEIS-v1-2011-SantosP #mining #preprocessor #ubiquitous
Enabling Ubiquitous Data Mining in Intensive Care — Features Selection and Data Pre-processing (MS, FP), pp. 261–266.
ICEISICEIS-v1-2011-ThitiprayoonwongseSS #mining
Data Mining on Dengue Virus Disease (DT, PS, NS), pp. 32–41.
CIKMCIKM-2011-OrdonezG #database #mining #query #relational #sql
A data mining system based on SQL queries and UDFs for relational databases (CO, CGA), pp. 2521–2524.
KDDKDD-2011-BatistaKMR #mining
SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining (GEAPAB, EJK, AMN, ER), pp. 761–764.
KDDKDD-2011-Bie #framework #mining
An information theoretic framework for data mining (TDB), pp. 564–572.
KDDKDD-2011-Boire #case study #lessons learnt #mining
The practitioner’s viewpoint to data mining: key lessons learned in the trenches and case studies (RB), p. 785.
KDDKDD-2011-GhotingKPK #algorithm #implementation #machine learning #mining #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.
KDDKDD-2011-Inchiosa #mining #scalability #using
Accelerating large-scale data mining using in-database analytics (MEI), p. 778.
KDDKDD-2011-KaufmanRP #detection #mining
Leakage in data mining: formulation, detection, and avoidance (SK, SR, CP), pp. 556–563.
KDDKDD-2011-McCloskeyKIKB #behaviour #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.
KDDKDD-2011-MohammedCFY #mining
Differentially private data release for data mining (NM, RC, BCMF, PSY), pp. 493–501.
KDDKDD-2011-Rejto #information management #mining #research
Knowledge discovery and data mining in pharmaceutical cancer research (PAR), p. 781.
KDDKDD-2011-VijayaraghavanK #machine learning #mining #online
Applications of data mining and machine learning in online customer care (RV, PVK), p. 779.
KDDKDD-2011-ZhengSTLLC #challenge #information management #mining #mobile
Applying data mining techniques to address disaster information management challenges on mobile devices (LZ, CS, LT, TL, SL, SCC), pp. 283–291.
MLDMMLDM-2011-TalbertHT #framework #machine learning #mining
A Machine Learning and Data Mining Framework to Enable Evolutionary Improvement in Trauma Triage (DAT, MH, ST), pp. 348–361.
SEKESEKE-2011-CellierDFR #fault #locality #mining #multi
Multiple Fault Localization with Data Mining (PC, MD, SF, OR), pp. 238–243.
SEKESEKE-2011-WuXKP #analysis #debugging #mining #named #reliability
BUGMINER: Software Reliability Analysis Via Data Mining of Bug Reports (LW, BX, GEK, RJP), pp. 95–100.
PDPPDP-2011-CesarioT #distributed #framework #grid #mining
A Failure Handling Framework for Distributed Data Mining Services on the Grid (EC, DT), pp. 70–79.
SIGMODSIGMOD-2010-OrdonezG #database #mining #research
Database systems research on data mining (CO, JGG), pp. 1253–1254.
EDMEDM-2010-BernauerP #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.
EDMEDM-2010-DominguezYC #generative #mining #python
Data Mining for Generating Hints in a Python Tutor (AKD, KY, JRC), pp. 91–100.
EDMEDM-2010-FalakmasirH #education #mining #using
Using Educational Data Mining Methods to Study the Impact of Virtual Classroom in E-Learning (MHF, JH), pp. 241–248.
EDMEDM-2010-KrugerMW10a #data analysis #mining
When Data Exploration and Data Mining meet while Analysing Usage Data of a Course (AK, AM, BW), pp. 305–306.
EDMEDM-2010-VialardiCBVEPO #case study #mining #student
A Case Study: Data Mining Applied to Student Enrollment (CVS, JC, AB, DV, JE, JPP, AO), pp. 333–334.
MSRMSR-2010-NussbaumZ #assurance #database #metadata #mining #quality
The Ultimate Debian Database: Consolidating bazaar metadata for Quality Assurance and data mining (LN, SZ), pp. 52–61.
ICEISICEIS-AIDSS-2010-CarvalhoSP #mining
Swarm Intelligence for Rule Discovery in Data Mining (ABdC, TS, AP), pp. 314–319.
ICEISICEIS-AIDSS-2010-Vilas-BoasSPSR #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.
ICEISICEIS-DISI-2010-ZhangOCK #case study #education #mining #student
Use Data Mining to Improve Student Retention in Higher Education — A Case Study (YZ, SO, TC, HK), pp. 190–197.
ICEISICEIS-ISAS-2010-EliceguiVM #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.
KDDKDD-2010-Feldman #lessons learnt #mining #quantifier #scalability
The quantification of advertising: (+ lessons from building businesses based on large scale data mining) (KF), pp. 5–6.
KDDKDD-2010-FriedmanS #difference #mining #privacy
Data mining with differential privacy (AF, AS), pp. 493–502.
KDDKDD-2010-KarguptaGF #generative #mining
The next generation of transportation systems, greenhouse emissions, and data mining (HK, JG, WF), pp. 1209–1212.
KDDKDD-2010-KarguptaSG #distributed #mining #overview #performance
MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system (HK, KS, MG), pp. 37–46.
KDDKDD-2010-KumarGM #fault #health #mining #predict
Data mining to predict and prevent errors in health insurance claims processing (MK, RG, ZSM), pp. 65–74.
KDDKDD-2010-Lu #industrial #mining #online
Data mining in the online services industry (QL), pp. 1–2.
KDDKDD-2010-YangNSS #mining #privacy
Collusion-resistant privacy-preserving data mining (BY, HN, IS, JS), pp. 483–492.
KDDKDD-2010-ZhengSTLLCH #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.
KDIRKDIR-2010-AchaKV #analysis #mining #modelling
Tactical Analysis Modeling through Data Mining — Pattern Discovery in Racket Sports (ATA, WAK, JKV), pp. 176–181.
KDIRKDIR-2010-CorreiaCL #architecture #collaboration #mining
An Architecture for Collaborative Data Mining (FC, RC, JCL), pp. 467–470.
KDIRKDIR-2010-Rauch #logic #mining #semantics #web
Logic of Discovery, Data Mining and Semantic Web — Position Paper (JR), pp. 342–351.
KDIRKDIR-2010-Vazquez-RodriguezPGFC #mining #visual notation
A New Visual Data Mining Tool for gvSIG GIS (RVR, CPR, IYGH, AFM, JCTC), pp. 428–431.
SEKESEKE-2010-SilvaS #classification #knowledge base #mining #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.
SACSAC-2010-CeciALM #approach #mining #ranking #relational
Complex objects ranking: a relational data mining approach (MC, AA, CL, DM), pp. 1071–1077.
SACSAC-2010-ChengSMZ #database #integration #mining #named #online
PROM-OOGLE: data mining and integration of on-line databases to discover gene promoters (DC, JS, MMP, ORZ), pp. 1547–1551.
SACSAC-2010-KatevaLRSTR #architecture #mining
SE-155 DBSA: a device-based software architecture for data mining (JK, PL, TR, JS, LT, JR), pp. 2273–2280.
SACSAC-2010-MarinhoCDFBBL #education #framework #mining #ontology
An ontology-based software framework to provide educational data mining (TM, EdBC, DD, RF, LMB, IIB, HPLL), pp. 1433–1437.
DATEDATE-2010-VasudevanSPTTJ #automation #generative #mining #named #static analysis #using
GoldMine: Automatic assertion generation using data mining and static analysis (SV, DS, SJP, DT, WT, DRJ), pp. 626–629.
PDPPDP-2010-KomashinskiyK #detection #mining
Malware Detection by Data Mining Techniques Based on Positionally Dependent Features (DK, IVK), pp. 617–623.
ICDARICDAR-2009-KizuYTGS #2d #mining
2D CAD Data Mining Based on Spatial Relation (HK, JY, TT, KG, NS), pp. 326–330.
SIGMODSIGMOD-2009-WangYGYTWLP #case study #communication #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.
EDMEDM-2009-AnayaB #approach #collaboration #framework #mining
A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks (ARA, JB), pp. 210–219.
EDMEDM-2009-RomeroVGCG #collaboration #education #mining
Collaborative Data Mining Tool for Education (CR, SV, EG, CdC, MG), pp. 299–308.
EDMEDM-2009-SacinASO #education #mining #recommendation #using
Recommendation in Higher Education Using Data Mining Techniques (CVS, JBA, LS, AO), pp. 191–199.
CoGCIG-2009-WeberM #approach #mining #predict
A data mining approach to strategy prediction (BGW, MM), pp. 140–147.
HCIDHM-2009-NamA #image #mining
Data Mining of Image Segments Data with Reduced Neurofuzzy System (DHN, EA), pp. 710–716.
HCIHIMI-DIE-2009-HorvathLK #analysis #approach #mining #usability
Usability Analyses of CRM Systems in Call Centers: The Data Mining Approach (ÁH, LL, AK), pp. 40–48.
ICEISICEIS-AIDSS-2009-BratuP #mining #preprocessor #towards
Towards a Unified Strategy for the Preprocessing Step in Data Mining (CVB, RP), pp. 230–235.
ICEISICEIS-AIDSS-2009-ChenC #mining
The Role of Data Mining Techniques in Emergency Management (NC, AC), pp. 118–123.
ICEISICEIS-J-2009-CunhaAM #mining #reuse
Knowledge Reuse in Data Mining Projects and Its Practical Applications (RCLVC, PJLA, SRdLM), pp. 317–324.
ICEISICEIS-J-2009-FritzscheML #analysis #concept #design #industrial #interactive #mining #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.
CIKMCIKM-2009-ChenPBSM #exclamation #lessons learnt #mining
Practical lessons of data mining at Yahoo! (YC, DP, PB, AS, AM), pp. 1047–1056.
CIKMCIKM-2009-PitonBBG #mining
Domain driven data mining to improve promotional campaign ROI and select marketing channels (TP, JB, HB, FG), pp. 1057–1066.
KDDKDD-2009-DaruruMWG #clustering #data flow #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.
KDDKDD-2009-Hand #mining #modelling #tool support
Mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools (DJH), pp. 1–2.
KDDKDD-2009-HanhijarviOVPTM #mining
Tell me something I don’t know: randomization strategies for iterative data mining (SH, MO, NV, KP, NT, HM), pp. 379–388.
KDDKDD-2009-Last #mining
Improving data mining utility with projective sampling (ML), pp. 487–496.
KDDKDD-2009-Mannila #mining
Randomization methods in data mining (HM), pp. 5–6.
KDDKDD-2009-PatnaikMSR #mining #using
Sustainable operation and management of data center chillers using temporal data mining (DP, MM, RKS, NR), pp. 1305–1314.
KDDKDD-2009-Srivastava #mining
Data mining at NASA: from theory to applications (ANS), pp. 7–8.
KDDKDD-2009-YeK #mining
Time series shapelets: a new primitive for data mining (LY, EJK), pp. 947–956.
KDIRKDIR-2009-PenaVP #mining
Explorative Data Mining for the Sizing of Population Groups (IP, HLV, EP), pp. 152–159.
KDIRKDIR-2009-WohrerZDB #composition #metaprogramming #mining #optimisation #towards
Unboxing Data Mining Via Decomposition in Operators — Towards Macro Optimization and Distribution (AW, YZ, EuHD, PB), pp. 243–248.
KDIRKDIR-2009-Zhan #collaboration #mining #privacy
Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
KEODKEOD-2009-Zhan #collaboration #mining #privacy
Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
KMISKMIS-2009-Zhan #collaboration #mining #privacy
Privacy-Preserving Collaborative Data Mining (JZ), p. 15.
MLDMMLDM-2009-FernandezBFM #automation #mining
Assisting Data Mining through Automated Planning (FF, DB, SF, DMM), pp. 760–774.
SEKESEKE-2009-AlvaresOHB #framework #mining #preprocessor
A Framework for Trajectory Data Preprocessing for Data Mining (LOA, GO, CAH, VB), pp. 698–702.
SEKESEKE-2009-CellierDFR #fault #locality #mining #named #process
DeLLIS: A Data Mining Process for Fault Localization (PC, MD, SF, OR), pp. 432–437.
PPoPPPPoPP-2009-MaA #compilation #mining #runtime
A compiler and runtime system for enabling data mining applications on gpus (WM, GA), pp. 287–288.
SIGMODSIGMOD-2008-Ramaswamy #mining
Extreme data mining (SR), pp. 1–2.
EDMEDM-2008-HubscherP #mining
Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge (RH, SP), pp. 97–106.
EDMEDM-2008-RomeroVEH #algorithm #mining #student
Data Mining Algorithms to Classify Students (CR, SV, PGE, CH), pp. 8–17.
SIGITESIGITE-2008-Kalathur #education #experience #mining #online #student
Enriching student experience with student driven content while teaching an online data mining class (SK), pp. 125–130.
MSRMSR-2008-Bernstein #how #mining
How to learn enough data mining to be dangerous in 60 minutes (AB), pp. 77–78.
ICEISICEIS-AIDSS-2008-BiscarriMLGBM #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.
ICEISICEIS-AIDSS-2008-BrissonC #mining #ontology #process
An Ontology Driven Data Mining Process (LB, MC), pp. 54–61.
ICEISICEIS-AIDSS-2008-JansLV #case study #mining #reduction
Internal Fraud Risk Reduction — Results of a Data Mining Case Study (MJ, NL, KV), pp. 161–166.
ICEISICEIS-DISI-2008-Gorea #architecture #concept #mining #modelling #named #web
DeVisa — Concepts and Architecture of a Data Mining Models Scoring and Management Web System (DG), pp. 276–281.
ICEISICEIS-ISAS2-2008-SchultK #adaptation #automation #concept #enterprise #mining #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.
ICEISICEIS-J-2008-BrissonC08a #how #mining #process #question #semantics
How to Semantically Enhance a Data Mining Process? (LB, MC), pp. 103–116.
CIKMCIKM-2008-Agrawal #mining
Humane data mining (RA), pp. 1–2.
KDDKDD-2008-ChoRC #identification #mining #network
Reconstructing chemical reaction networks: data mining meets system identification (YJC, NR, YC), pp. 142–150.
KDDKDD-2008-GrossmanG #mining #performance #using
Data mining using high performance data clouds: experimental studies using sector and sphere (RLG, YG), pp. 920–927.
KDDKDD-2008-KotsifakosNVT #mining #modelling #named
Pattern-Miner: integrated management and mining over data mining models (EEK, IN, YV, YT), pp. 1081–1084.
KDDKDD-2008-PedreschiRT #mining
Discrimination-aware data mining (DP, SR, FT), pp. 560–568.
KDDKDD-2008-ShengPI #mining #multi #quality #using
Get another label? improving data quality and data mining using multiple, noisy labelers (VSS, FJP, PGI), pp. 614–622.
RERE-2008-Castro-HerreraDCM #elicitation #mining #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.
HPDCHPDC-2008-ShrinivasN #detection #grid #mining
Issues in applying data mining to grid job failure detection and diagnosis (LS, JFN), pp. 239–240.
PDPPDP-2008-GrossF #communication #feedback #mining #named #ubiquitous
CoDaMine: Communication Data Mining for Feedback and Control in Ubiquitous Environments (TG, MF), pp. 539–546.
ICDARICDAR-2007-CeciBPM #approach #detection #mining #order
A Data Mining Approach to Reading Order Detection (MC, MB, GP, DM), pp. 924–928.
SIGMODSIGMOD-2007-VardeRS #mining #named #optimisation #process #visual notation
AutoDomainMine: a graphical data mining system for process optimization (ASV, EAR, RDSJ), pp. 1103–1105.
MSRMSR-2007-WeissgerberPB #detection #developer #how #mining #visual notation
Visual Data Mining in Software Archives to Detect How Developers Work Together (PW, MP, MB), p. 9.
WCREWCRE-2007-RaberL #debugging #mining #using
Emulated Breakpoint Debugger and Data Mining Using Detours (JR, EL), pp. 271–272.
HCIHCI-AS-2007-XueL #distributed #mining #modelling #research #similarity
Research of Distributed Data Mining Association Rules Model Based on Similarity (SX, ZL), pp. 1180–1189.
HCIHIMI-MTT-2007-NishimuraH #approach #case study #fault #mining #visualisation
The Study of Past Working History Visualization for Supporting Trial and Error Approach in Data Mining (KN, MH), pp. 327–334.
ICEISICEIS-AIDSS-2007-SokolovaF #architecture #assessment #mining #multi
A Multi-Agent Architecture for Environmental Impact Assessment: Information Fusion, Data Mining and Decision Making (MVS, AFC), pp. 219–224.
ICEISICEIS-AIDSS-2007-WanzellerB #assessment #mining #similarity
Similarity Assessment in a CBR Application for Clickstream Data Mining Plans Selection (CW, OB), pp. 137–144.
KDDKDD-2007-CotofreiS #mining #probability #process
Stochastic processes and temporal data mining (PC, KS), pp. 183–190.
KDDKDD-2007-GaoESCX #consistency #mining #problem #set
The minimum consistent subset cover problem and its applications in data mining (BJG, ME, JyC, OS, HX), pp. 310–319.
KDDKDD-2007-GuoZXF #database #learning #mining #multimodal
Enhanced max margin learning on multimodal data mining in a multimedia database (ZG, ZZ, EPX, CF), pp. 340–349.
KDDKDD-2007-Parthasarathy #learning #mining
Data mining at the crossroads: successes, failures and learning from them (SP), pp. 1053–1055.
MLDMMLDM-2007-SadoddinG #case study #comparative #detection #machine learning #mining
A Comparative Study of Unsupervised Machine Learning and Data Mining Techniques for Intrusion Detection (RS, AAG), pp. 404–418.
MLDMMLDM-2007-TanN #mining #privacy #probability #re-engineering
Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining (VYFT, SKN), pp. 76–90.
SACSAC-2007-FattaF #distributed #mining #multi
A customizable multi-agent system for distributed data mining (GDF, GF), pp. 42–47.
CASECASE-2007-RamachandranEMB #health #mining
Data Mining in Military Health Systems — Clinical and Administrative Applications (SR, ME, RJM, PCB), pp. 158–163.
DACDAC-2007-WangBA #correlation #mining #perspective
Design-Silicon Timing Correlation A Data Mining Perspective (LCW, PB, MSA), pp. 384–389.
DATEDATE-2007-BabighianKV #interactive #mining #optimisation
Interactive presentation: PowerQuest: trace driven data mining for power optimization (PB, GK, MYV), pp. 1078–1083.
VLDBVLDB-2006-LeglerLR #mining
Data Mining with the SAP Netweaver BI Accelerator (TL, WL, AR), pp. 1059–1068.
ITiCSEITiCSE-2006-MarkovR #mining
An introduction to the WEKA data mining system (ZM, IR), pp. 367–368.
ICEISICEIS-AIDSS-2006-BoudjeloudP #interactive #mining
Semi Interactive Method for Data Mining (LB, FP), pp. 3–10.
ICEISICEIS-AIDSS-2006-GollerHS #algorithm #mining
Beneficial Sequential Combination of Data Mining Algorithms (MG, MH, MS), pp. 135–143.
ICEISICEIS-AIDSS-2006-PintoGS #database #mining #paradigm
Data Mining as a New Paradigm for Business Intelligence in Database Marketing Projects (FMP, PG, MFS), pp. 144–149.
ICEISICEIS-HCI-2006-BadjioP #analysis #mining #process #visual notation
Context of Use Analysis — Activity Checklist for Visual Data Mining (EPFB, FP), pp. 45–50.
ICPRICPR-v1-2006-CantoniLL #challenge #distributed #mining #network
Challenges for Data Mining in Distributed Sensor Networks (VC, LL, PL), pp. 1000–1007.
ICPRICPR-v3-2006-VilchesEVT #mining #recognition
Data Mining Applied to Acoustic Bird Species Recognition (EV, IAE, EEV, CET), pp. 400–403.
KDDKDD-2006-AggarwalPZ #mining #on the #privacy
On privacy preservation against adversarial data mining (CCA, JP, BZ), pp. 510–516.
KDDKDD-2006-Cavaretta #challenge #mining
Data mining challenges in the automotive domain (MC), p. 836.
KDDKDD-2006-GionisMMT #mining
Assessing data mining results via swap randomization (AG, HM, TM, PT), pp. 167–176.
KDDKDD-2006-ManiyarN #algorithm #mining #using #visual notation #visualisation
Visual data mining using principled projection algorithms and information visualization techniques (DMM, ITN), pp. 643–648.
KDDKDD-2006-McCallum #information management #mining
Information extraction, data mining and joint inference (AM), p. 835.
KDDKDD-2006-MierswaWKSE #agile #mining #named #prototype
YALE: rapid prototyping for complex data mining tasks (IM, MW, RK, MS, TE), pp. 935–940.
KDDKDD-2006-Piatetsky-ShapiroGDFGZ #challenge #mining #question
Is there a grand challenge or X-prize for data mining? (GPS, RG, CD, RF, LG, MJZ), pp. 954–956.
KDDKDD-2006-ZhaoLBX #identification #mining
Opportunity map: identifying causes of failure — a deployed data mining system (KZ, BL, JB, WX), pp. 892–901.
SEKESEKE-2006-CazellaA #architecture #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.
SEKESEKE-2006-HungL #mining #performance #using
Using Data Mining Schemes for Improvement on System Performance in Virtual Environments (SSH, DSML), pp. 61–66.
SACSAC-2006-AbidinP #classification #mining #named #nearest neighbour #performance #scalability
SMART-TV: a fast and scalable nearest neighbor based classifier for data mining (TA, WP), pp. 536–540.
SACSAC-2006-GamaP #data type #mining
Discretization from data streams: applications to histograms and data mining (JG, CP), pp. 662–667.
SACSAC-2006-GuoW #mining #on the #privacy #using
On the use of spectral filtering for privacy preserving data mining (SG, XW), pp. 622–626.
SACSAC-2006-MaC #algorithm #array #mining #network #novel
A novel data mining algorithm for reconstructing gene regulatory networks from microarray data (PCHM, KCCC), pp. 202–203.
HPCAHPCA-2006-JaleelMJ #case study #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.
HPDCHPDC-2006-CieslakTC #distributed #mining
Troubleshooting Distributed Systems via Data Mining (DAC, DT, NVC), pp. 309–312.
HPDCHPDC-2006-DuanPF #detection #fault #grid #predict
Data Mining-based Fault Prediction and Detection on the Grid (RD, RP, TF), pp. 305–308.
PODSPODS-2005-LiLWFT #mining #perspective
Relative risk and odds ratio: a data mining perspective (HL, JL, LW, MF, YPT), pp. 368–377.
ITiCSEITiCSE-2005-Roiger #education #mining
Teaching an introductory course in data mining (RJR), p. 415.
TLCATLCA-2005-MatwinFHC #formal method #mining #privacy #using
Privacy in Data Mining Using Formal Methods (SM, APF, ITH, VC), pp. 278–292.
SOFTVISSOFTVIS-2005-BurchDW #mining #visual notation
Visual data mining in software archives (MB, SD, PW), pp. 37–46.
ICEISICEIS-v2-2005-KianmehrZNOA #approach #mining #network
Combining Neural Network and Support Vector Machine into Integrated Approach for Biodata Mining (KK, HZ, KN, , RA), pp. 182–187.
ICEISICEIS-v2-2005-SantosPS #clustering #framework #mining #modelling
A Cluster Framework for Data Mining Models — An Application to Intensive Medicine (MFS, JP, ÁMS), pp. 163–168.
ICEISICEIS-v3-2005-EspositoMORS #detection #mining #novel #realtime
Real Time Detection of Novel Attacks by Means of Data Mining Techniques (ME, CM, FO, SPR, CS), pp. 120–127.
ICEISICEIS-v5-2005-BadjioP #metric #mining #quality #tool support #visual notation
Visual Data Mining Tools: Quality Metrics Definition and Application (EPFB, FP), pp. 98–103.
KDDKDD-2005-KalosR #industrial #mining
Data mining in the chemical industry (ANK, TR), pp. 763–769.
MLDMMLDM-2005-KuhlmannVLT #mining #simulation
Data Mining on Crash Simulation Data (AK, RMV, CL, CAT), pp. 558–569.
MLDMMLDM-2005-MottlKSM #kernel #mining #multi
Principles of Multi-kernel Data Mining (VM, OK, OS, IBM), pp. 52–61.
MLDMMLDM-2005-XiaWZL #mining #modelling #random
Mixture Random Effect Model Based Meta-analysis for Medical Data Mining (YX, SW, CZ, SL), pp. 630–640.
SEKESEKE-2005-BogornyEA #framework #mining
A Reuse-based Spatial Data Preparation Framework for Data Mining (VB, PME, LOA), pp. 649–652.
SEKESEKE-2005-ChanS #mining #rule-based
From Data to Knowledge: an Integrated Rule-Based Data Mining System (CCC, ZS), pp. 508–513.
ASEASE-2005-DenmatDR #execution #mining
Data mining and cross-checking of execution traces: a re-interpretation of Jones, Harrold and Stasko test information (TD, MD, OR), pp. 396–399.
PPoPPPPoPP-2005-CongHHP #framework #mining #parallel
A sampling-based framework for parallel data mining (SC, JH, JH, DAP), pp. 255–265.
VLDBVLDB-2004-AgrawalS #mining #question
Whither Data Mining? (RA, RS), p. 9.
IWPCIWPC-2004-KanellopoulosT #c++ #clustering #comprehension #mining #source code
Data Mining Source Code to Facilitate Program Comprehension: Experiments on Clustering Data Retrieved from C++ Programs (YK, CT), pp. 214–225.
ICEISICEIS-v2-2004-BangDHD #concept #effectiveness #framework #knowledge base #mining #segmentation
Data Mining of CRM Knowledge Bases for Effective Market Segmentation: A Conceptual Framework (JB, ND, LH, RRD), pp. 335–342.
ICEISICEIS-v2-2004-DoP #mining #tool support #towards #visualisation
Towards High Dimensional Data Mining with Boosting of PSVM and Visualization Tools (TND, FP), pp. 36–41.
ICEISICEIS-v2-2004-KuusikLV #clique #mining
Data Mining: Pattern Mining as a Clique Extracting Task (RK, GL, LV), pp. 519–522.
ICEISICEIS-v2-2004-MataRR #case study #development #mining
Applying Data Mining to Software Development Projects: A Case Study (JMV, JLÁM, JCRS, IR), pp. 54–60.
ICEISICEIS-v2-2004-Poulet #mining #towards #visual notation
Towards Visual Data Mining (FP), pp. 349–356.
ICEISICEIS-v2-2004-ZarateAPR #mining
Data Mining Application to Obtain Profiles of Patients with Nephrolithiasis (LEZ, PA, RP, TR), pp. 104–109.
ICEISICEIS-v4-2004-LimaEMFC #information management #mining #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.
ICEISICEIS-v5-2004-BadjioP #mining #tool support #usability #visual notation
Usability of Visual Data Mining Tools (EPFB, FP), pp. 254–258.
ICEISICEIS-v5-2004-JantkeLGGTT #learning #mining
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.
KDDKDD-2004-AbajoDLC #case study #delivery #industrial #mining #modelling #quality
ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study (NdA, ABD, VL, SRC), pp. 799–804.
KDDKDD-2004-CaruanaN #analysis #empirical #learning #metric #mining #performance
Data mining in metric space: an empirical analysis of supervised learning performance criteria (RC, ANM), pp. 69–78.
KDDKDD-2004-DavidsonGST #algorithm #approach #matrix #mining #quality
A general approach to incorporate data quality matrices into data mining algorithms (ID, AG, AS, GKT), pp. 794–798.
KDDKDD-2004-EsterGJH #mining #problem #segmentation
A microeconomic data mining problem: customer-oriented catalog segmentation (ME, RG, WJ, ZH), pp. 557–562.
KDDKDD-2004-Heckerman #mining #modelling #visual notation
Graphical models for data mining (DH), p. 2.
KDDKDD-2004-KantarciogluJC #mining #privacy #question
When do data mining results violate privacy? (MK, JJ, CC), pp. 599–604.
KDDKDD-2004-KeoghLR #mining #towards
Towards parameter-free data mining (EJK, SL, C(R), pp. 206–215.
KDDKDD-2004-ZhangZK #approach #category theory #image #mining #modelling
A data mining approach to modeling relationships among categories in image collection (RZ, Z(Z, SK), pp. 749–754.
KDDKDD-2004-ZhuL #mining #privacy
Optimal randomization for privacy preserving data mining (MYZ, LL), pp. 761–766.
SACSAC-2004-HuP #approach #database #detection #mining
A data mining approach for database intrusion detection (YH, BP), pp. 711–716.
HPDCHPDC-2004-GilburdSW #mining #privacy
Privacy-Preserving Data Mining on Data Grids in the Presence of Malicious Participants (BG, AS, RW), pp. 225–234.
PDPPDP-2004-BorzemskiLN #analysis #internet #mining #performance
Application of Data Mining for the Analysis of Internet Path Performance (LB, LL, ZN), pp. 54–59.
JCDLJCDL-2003-LeroyCMEFKHLXMN #mining #named
Genescene: Biomedical Text And Data Mining (GL, HC, JDM, SE, RRF, KLK, ZH, JL, JJX, DM, TGN), pp. 116–118.
PODSPODS-2003-EvfimievskiGS #mining #privacy
Limiting privacy breaches in privacy preserving data mining (AVE, JG, RS), pp. 211–222.
PODSPODS-2003-RameshMZ #mining #theory and practice
Feasible itemset distributions in data mining: theory and application (GR, WM, MJZ), pp. 284–295.
VLDBVLDB-2003-HinneburgLH #database #mining #named
COMBI-Operator: Database Support for Data Mining Applications (AH, WL, DH), pp. 429–439.
VLDBVLDB-2003-LubbersGJ #development #quality #tool support
Systematic Development of Data Mining-Based Data Quality Tools (DL, UG, MJ), pp. 548–559.
VLDBVLDB-2003-WangZL #data type #mining #named #sql
ATLAS: A Small but Complete SQL Extension for Data Mining and Data Streams (HW, CZ, CL), pp. 1113–1116.
ICEISICEIS-v2-2003-GalianoCMSB #mining #usability
Usability Issues in Data Mining Systems (FBG, JCC, NM, JMS, IJB), pp. 418–421.
ICEISICEIS-v2-2003-KrolikowskiMP #mining #query
Set-Oriented Indexes for Data Mining Queries (ZK, MM, JP), pp. 316–323.
ICEISICEIS-v2-2003-KuusikL #approach #mining #using
An Approach of Data Mining Using Monotone Systems (RK, GL), pp. 482–485.
ICEISICEIS-v2-2003-MaciasVSR #development #mining
A Data Mining Method to Support Decision Making in Software Development Projects (JLÁM, JMV, JCRS, IR), pp. 11–18.
ICEISICEIS-v2-2003-PetitP #approach #mining
A New Approach of Data Mining: The Meta Projectories (CP, SP), pp. 515–518.
ICEISICEIS-v3-2003-HoangHB #detection #mining
Intrusion Detection Based on Data Mining (XDH, JH, PB), pp. 341–346.
KDDKDD-2003-Aggarwal #design #distance #mining #towards
Towards systematic design of distance functions for data mining applications (CCA), pp. 9–18.
KDDKDD-2003-DuZ #mining #privacy #random #using
Using randomized response techniques for privacy-preserving data mining (WD, JZZ), pp. 505–510.
KDDKDD-2003-FramAD #empirical #mining #safety
Empirical Bayesian data mining for discovering patterns in post-marketing drug safety (DMF, JSA, WD), pp. 359–368.
KDDKDD-2003-LastFK #approach #automation #mining #testing
The data mining approach to automated software testing (ML, MF, AK), pp. 388–396.
KDDKDD-2003-SequeiraZSC #locality #mining #source code
Improving spatial locality of programs via data mining (KS, MJZ, BKS, CDC), pp. 649–654.
KDDKDD-2003-WeissBKD #knowledge-based #mining
Knowledge-based data mining (SMW, SJB, SK, SD), pp. 456–461.
KDDKDD-2003-YiLL #mining #web
Eliminating noisy information in Web pages for data mining (LY, BL, XL), pp. 296–305.
KDDKDD-2003-ZhangSY #mining
Applying data mining in investigating money laundering crimes (Z(Z, JJS, PSY), pp. 747–752.
MLDMMLDM-2003-Bunke #graph #machine learning #mining #tool support
Graph-Based Tools for Data Mining and Machine Learning (HB), pp. 7–19.
SEKESEKE-2003-ChapinK #metric #mining #re-engineering
Validative measurement in software engineering: a data mining example (NC, MKM), pp. 626–633.
SEKESEKE-2003-WuS #approach #mining
A Data Mining Approach for Dynamic Software Project Plan Tracking (CSW, DBS), pp. 634–638.
PADLPADL-2003-ClareK #functional #lazy evaluation #mining
Data Mining the Yeast Genome in a Lazy Functional Language (AC, RDK), pp. 19–36.
SACSAC-2003-BarbaraLLJC #detection #mining
Bootstrapping a Data Mining Intrusion Detection System (DB, YL, JLL, SJ, JC), pp. 421–425.
SACSAC-2003-HuaJVT #algebra #analysis #approach #mining #named #performance #using
ADMiRe: An Algebraic Approach to System Performance Analysis Using Data Mining Techniques (KAH, NJ, RV, DAT), pp. 490–496.
SACSAC-2003-LiZO #distributed #mining #modelling #similarity
A New Distributed Data Mining Model Based on Similarity (TL, SZ, MO), pp. 432–436.
SACSAC-2003-Meo #mining #optimisation
Optimization of a Language for Data Mining (RM), pp. 437–444.
PPoPPPPoPP-2003-Kazar #mining #performance #scalability
High performance spatial data mining for very large data-sets (BMK), p. 1.
VLDBVLDB-2002-Faloutsos #analysis #mining #similarity
Sensor Data Mining: Similarity Search and Pattern Analysis (CF).
ICALPICALP-2002-Mannila #mining #problem
Local and Global Methods in Data Mining: Basic Techniques and Open Problems (HM), pp. 57–68.
ICEISICEIS-2002-CarrascoMG #flexibility #mining #named #query
FSQL: A Flexible Query Language for Data Mining (RAC, MAVM, JG), pp. 50–56.
ICEISICEIS-2002-KrishnaswamyLZ #distributed #mining #optimisation #predict #runtime
Supporting the Optimisation of Distributed Data Mining by Predicting Application Run Times (SK, SWL, ABZ), pp. 374–381.
ICEISICEIS-2002-MengYCC #information management #mining
Data Mining Mechanisms in Knowledge Management System (IHM, WPY, WCC, LPC), pp. 399–404.
ICEISICEIS-2002-SanchezSVACD #mining #using
Using Data Mining Techniques to Analyze Correspondences between Partitions (DS, JMS, MAVM, VA, JC, GD), pp. 179–186.
ICEISICEIS-2002-SantosNASR #classification #database #learning #mining #using
Augmented Data Mining over Clinical Databases Using Learning Classifier Systems (MFS, JN, AA, ÁMS, FR), pp. 512–516.
ICEISICEIS-2002-TanTS #mining #parallel #performance #taxonomy
A Taxonomy for Inter-Model Parallelism in High Performance Data Mining (LT, DT, KAS), pp. 534–539.
CIKMCIKM-2002-Faloutsos #mining #network #self
Future directions in data mining: streams, networks, self-similarity and power laws (CF), p. 93.
CIKMCIKM-2002-PanF #library #mining #quote #video
“GeoPlot”: spatial data mining on video libraries (JYP, CF), pp. 405–412.
KDDKDD-2002-AlqallafKMZ #correlation #mining #robust #scalability
Scalable robust covariance and correlation estimates for data mining (FAA, KPK, RDM, RHZ), pp. 14–23.
KDDKDD-2002-KeoghK #benchmark #empirical #metric #mining #on the #overview
On the need for time series data mining benchmarks: a survey and empirical demonstration (EJK, SK), pp. 102–111.
KDDKDD-2002-LinLCY #database #distributed #mining #transaction
Distributed data mining in a chain store database of short transactions (CRL, CHL, MSC, PSY), pp. 576–581.
KDDKDD-2002-LittleJLRS #mining
Collusion in the U.S. crop insurance program: applied data mining (BBL, WLJ, ACL, RMR, SAS), pp. 594–598.
KDDKDD-2002-PalmerGF #graph #mining #named #performance #scalability
ANF: a fast and scalable tool for data mining in massive graphs (CRP, PBG, CF), pp. 81–90.
KDDKDD-2002-SequeiraZ #mining #named
ADMIT: anomaly-based data mining for intrusions (KS, MJZ), pp. 386–395.
KDDKDD-2002-WuFS #approach #classification #mining #named
B-EM: a classifier incorporating bootstrap with EM approach for data mining (XW, JF, KRS), pp. 670–675.
SEKESEKE-2002-PoleseTT #mining
A data mining based system supporting tactical decisions (GP, MT, GT), pp. 681–684.
SACSAC-2002-ChangJ #clustering #mining #scalability
A new cell-based clustering method for large, high-dimensional data in data mining applications (JWC, DSJ), pp. 503–507.
SACSAC-2002-Geist #framework #mining
A framework for data mining and KDD (IG), pp. 508–513.
SACSAC-2002-KrishnaswamyLZ #estimation #metric #mining #quality #runtime
Application run time estimation: a quality of service metric for web-based data mining services (SK, SWL, ABZ), pp. 1153–1159.
SACSAC-2002-WangW #approach #mining #optimisation #query #relational
Optimizing relational store for e-catalog queries: a data mining approach (MW, XSW), pp. 1147–1152.
DACDAC-2002-LiuSRC #design #megamodelling #mining #scalability
Remembrance of circuits past: macromodeling by data mining in large analog design spaces (HL, AS, RAR, LRC), pp. 437–442.
PODSPODS-2001-AgrawalA #algorithm #design #mining #on the #privacy #quantifier
On the Design and Quantification of Privacy Preserving Data Mining Algorithms (DA, CCA).
VLDBVLDB-2001-MargaritisFT #mining #named #performance #scalability
NetCube: A Scalable Tool for Fast Data Mining and Compression (DM, CF, ST), pp. 311–320.
VLDBVLDB-2001-SadriZZA #mining #query
A Sequential Pattern Query Language for Supporting Instant Data Mining for e-Services (RS, CZ, AMZ, JA), pp. 653–656.
ICEISICEIS-v1-2001-ThorntonR #artificial reality #mining #network #using
Using Virtual Reality Data Mining for Network Management (KEBT, CR), pp. 340–344.
KDDKDD-2001-AdderleyM #behaviour #case study #commit #mining #modelling
Data mining case study: modeling the behavior of offenders who commit serious sexual assaults (RA, PBM), pp. 215–220.
KDDKDD-2001-BujaL #classification #mining
Data mining criteria for tree-based regression and classification (AB, YSL), pp. 27–36.
KDDKDD-2001-Edelstein #mining #question
Data mining: are we there yet? (HE), p. 7.
KDDKDD-2001-Elkan #challenge #lessons learnt #mining
Magical thinking in data mining: lessons from CoIL challenge 2000 (CE), pp. 426–431.
KDDKDD-2001-GarckeG #mining #using
Data mining with sparse grids using simplicial basis functions (JG, MG), pp. 87–96.
KDDKDD-2001-HueglinV #mining
Data mining techniques to improve forecast accuracy in airline business (CH, FV), pp. 438–442.
KDDKDD-2001-Netz #database #developer #framework #mining #platform
Data mining platform for database developers (AN), p. 14.
KDDKDD-2001-Ramakrishnan #collaboration #mining
Mass collaboration and data mining (RR), p. 4.
KDDKDD-2001-TrainaTPF #mining #multi #named #scalability #tool support
Tri-plots: scalable tools for multidimensional data mining (AJMT, CTJ, SP, CF), pp. 184–193.
KDDKDD-T-2001-FayyadRB #enterprise #mining
E-business enterprise data mining (UMF, NR, PSB), pp. 1–85.
KDDKDD-T-2001-GallantPT #mining #web
Value-based data mining and web mining for CRM (SG, GPS, MT), pp. 325–390.
KDDKDD-T-2001-KarguptaJ #distributed #mining #mobile #ubiquitous
Data mining “to go”: ubiquitous KDD for mobile and distributed environments (HK, AJ), pp. 186–263.
KDDKDD-T-2001-Martin #mining #robust #statistics
Data mining for outliers with robust statistics (RDM), pp. 86–118.
LSOLSO-2001-KrishnaswamyLZ #elicitation #mining
Knowledge Elicitation through Web-Based Data Mining Services (SK, SWL, ABZ), pp. 120–134.
LSOLSO-2001-VossRMJ #collaboration #enterprise #mining
Collaboration Support for Virtual Data Mining Enterprises (AV, GR, SM, AJ), pp. 83–95.
MLDMMLDM-2001-PernerB #hybrid #mining
A Hybrid Tool for Data Mining in Picture Archiving System (PP, TPB), pp. 141–156.
MLDMMLDM-2001-SackK #evaluation #mining
Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining (US, MK), pp. 12–22.
MLDMMLDM-2001-SyG #analysis #approach #mining #statistics
Data Mining Approach Based on Information-Statistical Analysis: Application to Temporal-Spatial Data (BKS, AKG), pp. 128–140.
SEKESEKE-2001-AlonsoCGM #mining
Combining Expert Knowledge and Data Mining in a Medical Diagnosis Domain (FA, JPCV, ÁLG, CM), pp. 412–419.
TOOLSTOOLS-USA-2001-LiKLCL #algorithm #automation #mining #parallel
Automatic Data Mining by Asynchronous Parallel Evolutionary Algorithms (JL, ZK, YL, HC, PL), pp. 99–107.
ICSEICSE-2001-Michail #library #mining #named #reuse
CodeWeb: Data Mining Library Reuse Patterns (AM), pp. 827–828.
HPDCHPDC-2001-KuntrarukP #distributed #feature model #mining #parallel #using
Massively Parallel Distributed Feature Extraction in Textual Data Mining Using HDDI(tm) (JK, WMP), pp. 363–370.
SIGMODSIGMOD-2000-AgrawalS #mining #privacy
Privacy-Preserving Data Mining (RA, RS), pp. 439–450.
SIGMODSIGMOD-2000-PalmerF #clustering #mining
Density Biased Sampling: An Improved Method for Data Mining and Clustering (CRP, CF), pp. 82–92.
SIGMODSIGMOD-2000-PeiMHZ #benchmark #metric #mining #performance #towards
Towards Data Mining Benchmarking: A Testbed for Performance Study of Frequent Pattern Mining (JP, RM, KH, HZ), p. 592.
SIGMODSIGMOD-2000-RiedelFGN #for free #mining
Data Mining on an OLTP System (Nearly) for Free (ER, CF, GRG, DN), pp. 13–21.
VLDBVLDB-2000-ChoenniV #algorithm #design #implementation #mining
Design and Implementation of a Genetic-Based Algorithm for Data Mining (SC), pp. 33–42.
VLDBVLDB-2000-LakshmananJN #algebra #mining
The 3W Model and Algebra for Unified Data Mining (TJ, LVSL, RTN), pp. 21–32.
VLDBVLDB-2000-NetzCBF #database #integration #mining
Integration of Data Mining with Database Technology (AN, SC, JB, UMF), pp. 719–722.
VLDBVLDB-2000-Tsur #mining
Data Mining in the Bioinformatics Domain (ST), pp. 711–714.
CSMRCSMR-2000-SartipiKM #architecture #design #mining #using
Architectural Design Recovery using Data Mining Techniques (KS, KK, FM), pp. 129–140.
ICPRICPR-v1-2000-YouB #mining #retrieval
Dynamic Shape Retrieval by Hierarchical Curve Matching, Snakes and Data Mining (JY, PB), pp. 5035–5038.
KDDKDD-2000-BecherBF #automation #data analysis #mining #performance
Automating exploratory data analysis for efficient data mining (JDB, PB, EF), pp. 424–429.
KDDKDD-2000-Bhattacharyya #algorithm #mining #modelling #multi #performance
Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing (SB), pp. 465–473.
KDDKDD-2000-BrijsGSVW #framework #mining
A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model (TB, BG, GS, KV, GW), pp. 300–304.
KDDKDD-2000-Catlett #mining #privacy
Among those dark electronic mills: privacy and data mining (JC), p. 4.
KDDKDD-2000-DhondGV #mining #optimisation
Data mining techniques for optimizing inventories for electronic commerce (AD, AG, SV), pp. 480–486.
KDDKDD-2000-GardnerB #mining #problem
Data mining solves tough semiconductor manufacturing problems (MG, JB), pp. 376–383.
KDDKDD-2000-KingKCD #functional #mining #predict #sequence #using
Genome scale prediction of protein functional class from sequence using data mining (RDK, AK, AC, LD), pp. 384–389.
KDDKDD-2000-MaLWYL #mining #student #using
Targeting the right students using data mining (YM, BL, CKW, PSY, SML), pp. 457–464.
KDDKDD-2000-Papadimitriou #mining #on the
On certain rigorous approaches to data mining (CHP), p. 2.
KDDKDD-2000-PenaFL #behaviour #detection #mining
Data mining to detect abnormal behavior in aerospace data (JMP, FF, SL), pp. 390–397.
KDDKDD-2000-Stodder #mining
After the gold rush (invited talk, abstract only): data mining in the new economy (DS), p. 7.
KDDKDD-2000-TanBHG #mining
Textual data mining of service center call records (PNT, HB, SAH, RPG), pp. 417–423.
KDDKDD-2000-WangMSW #biology #case study #classification #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.
PADLPADL-2000-HuCT #algorithm #analysis #mining
Calculating a New Data Mining Algorithm for Market Basket Analysis (ZH, WNC, MT), pp. 169–184.
ICSEICSE-2000-Michail #library #mining #reuse #using
Data mining library reuse patterns using generalized association rules (AM), pp. 167–176.
SACSAC-2000-GoodwinM #mining #predict
Data Mining for Preterm Birth Prediction (LKG, SM), pp. 46–51.
HPDCHPDC-2000-HinkeN #grid #mining #power management
Data Mining on NASA’s Information Power Grid (THH, JN), pp. 292–293.
SIGMODSIGMOD-1999-Chakrabarti #database #hypermedia #mining
Hypertext Databases and Data Mining (SC), p. 508.
KDDKDD-1999-Agrawal #mining
Data Mining: Crossing the Chasm (RA), p. 2.
KDDKDD-1999-BayP #category theory #detection #mining #set
Detecting Change in Categorical Data: Mining Contrast Sets (SDB, MJP), pp. 302–306.
KDDKDD-1999-BuntineFP #automation #mining #source code #synthesis #towards
Towards Automated Synthesis of Data Mining Programs (WLB, BF, TP), pp. 372–376.
KDDKDD-1999-HotzNPS #industrial #mining
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.
KDDKDD-1999-ManiDBD #mining #modelling #statistics
Statistics and Data Mining Techniques for Lifetime Value Modeling (DRM, JD, AB, PD), pp. 94–103.
KDDKDD-1999-WangWLSSZ #algorithm #clustering #mining
Evaluating a Class of Distance-Mapping Algorithms for Data Mining and Clustering (JTLW, XW, KIL, DS, BAS, KZ), pp. 307–311.
KDDKDD-T-1999-Holsheimer #mining #process
Data Mining by Business Users: Integrating Data Mining in Business Processes (MH), pp. 266–291.
MLDMMLDM-1999-HongW #mining #predict
Advanced in Predictive Data Mining Methods (SJH, SMW), pp. 13–20.
MLDMMLDM-1999-Sawaragi #effectiveness #interactive #mining
Reproductive Process-Oriented Data Mining from Interactions between Human and Complex Artifact System (TS), pp. 180–194.
MLDMMLDM-1999-Scaringella #mining #monitoring #risk management
A Data Mining Application for Monitoring Environmental Risks (AS), pp. 209–215.
ASEASE-1999-Michail #library #mining #reuse
Data Mining Library Reuse Patterns in User-Selected Applications (AM), p. 24–?.
ADLADL-1998-AhonenHKV #documentation #mining
Applying Data Mining Techniques for Descriptive Phrase Extraction in Digital Document Collections (HA, OH, MK, AIV), pp. 2–11.
ADLADL-1998-ZaianeXH #data access #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.
SIGMODSIGMOD-1998-AgrawalGGR #automation #clustering #mining
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications (RA, JG, DG, PR), pp. 94–105.
SIGMODSIGMOD-1998-LiS #mining #parallel
Free Parallel Data Mining (BL, DS), pp. 541–543.
SIGMODSIGMOD-1998-NgLK #mining
A Data Mining Application: Customes Retention at the Port of Singapore Authority (PSA) (KN, HL, HK), pp. 522–525.
SIGMODSIGMOD-1998-ZaianeHLCC #mining #multi #named #prototype
MultiMediaMiner: A System Prototype for Multimedia Data Mining (ORZ, JH, ZNL, SHSC, JC), pp. 581–583.
VLDBVLDB-1998-George #mining #named #parallel
DMS: A Parallel Data Mining Server (FAWG), p. 702.
VLDBVLDB-1998-KornLKF #mining #paradigm #performance
Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining (FK, AL, YK, CF), pp. 582–593.
VLDBVLDB-1998-RiedelGF #mining #multi #scalability
Active Storage for Large-Scale Data Mining and Multimedia (ER, GAG, CF), pp. 62–73.
ICSMEICSM-1998-OcaC #identification #mining #using
Identification of Data Cohesive Subsystems Using Data Mining Techniques (CMdO, DLC), pp. 16–23.
KDDKDD-1998-BerchtoldJR #diagrams #independence #mining #visual notation
Independence Diagrams: A Technique for Visual Data Mining (SB, HVJ, KAR), pp. 139–143.
KDDKDD-1998-GrecuB #distributed #learning #mining
Coactive Learning for Distributed Data Mining (DLG, LAB), pp. 209–213.
KDDKDD-1998-KellyHA #mining #performance
Defining the Goals to Optimise Data Mining Performance (MGK, DJH, NMA), pp. 234–238.
KDDKDD-1998-LingL #mining #problem
Data Mining for Direct Marketing: Problems and Solutions (CXL, CL), pp. 73–79.
KDDKDD-1998-NakhaeizadehS #algorithm #evaluation #mining #personalisation #towards
Towards the Personalization of Algorithms Evaluation in Data Mining (GN, AS), pp. 289–293.
KDDKDD-1998-StaudtKR #mining
A Data Mining Support Environment and its Application on Insurance Data (MS, JUK, UR), pp. 105–111.
KDDKDD-1998-Subramonian #mining
Defining diff as a Data Mining Primitive (RS), pp. 334–338.
TOOLSTOOLS-ASIA-1998-WangH #implementation #mining #research
The Research and Implementation of Data Warehouse and Data Mining in Decision Support System (BW, JH), pp. 362–371.
SACSAC-1998-MachucaM #database #mining #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.
HPDCHPDC-1998-OguchiSTK #clustering #effectiveness #evaluation #mining #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.
PODSPODS-1997-GunopulosKMT #machine learning #mining
Data mining, Hypergraph Transversals, and Machine Learning (DG, RK, HM, HT), pp. 209–216.
SIGMODSIGMOD-1997-HanKK #mining #parallel #scalability
Scalable Parallel Data Mining for Association Rules (EHH, GK, VK), pp. 277–288.
SIGMODSIGMOD-1997-HanKS #mining #named #prototype
GeoMiner: A System Prototype for Spatial Data Mining (JH, KK, NS), pp. 553–556.
VLDBVLDB-1997-ShaferA #algorithm #mining #parallel #similarity
Parallel Algorithms for High-dimensional Similarity Joins for Data Mining Applications (JCS, RA), pp. 176–185.
VLDBVLDB-1997-WangYM #approach #grid #mining #named #statistics
STING: A Statistical Information Grid Approach to Spatial Data Mining (WW, JY, RRM), pp. 186–195.
CIKMCIKM-1997-YoonSP #mining #query #using
Intensional Query Processing Using Data Mining Approaches (SCY, IYS, EKP), pp. 201–208.
KDDKDD-1997-AronisP #algorithm #mining #performance
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation (JMA, FJP), pp. 119–122.
KDDKDD-1997-BergstenSS #analysis #machine learning #mining
Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis (UB, JS, PS), pp. 127–130.
KDDKDD-1997-BrunkKK #mining #named
MineSet: An Integrated System for Data Mining (CB, JK, RK), pp. 135–138.
KDDKDD-1997-ChattratichatDGGHKSTY #challenge #mining #scalability
Large Scale Data Mining: Challenges and Responses (JC, JD, MG, YG, HH, MK, JS, HWT, DY), pp. 143–146.
KDDKDD-1997-EngelsLS #mining
A Guided Tour through the Data Mining Jungle (RE, GL, RS), pp. 163–166.
KDDKDD-1997-FeldmanKZ #documentation #mining #visualisation
Visualization Techniques to Explore Data Mining Results for Document Collections (RF, WK, AZ), pp. 16–23.
KDDKDD-1997-KarguptaHS #architecture #distributed #mining #scalability
Scalable, Distributed Data Mining — An Agent Architecture (HK, IH, BS), pp. 211–214.
KDDKDD-1997-MihalisinT #mining #performance #robust #visual notation
Fast Robust Visual Data Mining (TM, JT), pp. 231–234.
KDDKDD-1997-NakhaeizadehS #algorithm #development #evaluation #metric #mining #multi
Development of Multi-Criteria Metrics for Evaluation of Data Mining Algorithms (GN, AS), pp. 37–42.
KDDKDD-1997-ZupanBBC #approach #composition #dataset #mining
A Dataset Decomposition Approach to Data Mining and Machine Discovery (BZ, MB, IB, BC), pp. 299–302.
TOOLSTOOLS-ASIA-1997-Dai #approach #database #integration #mining #multi #object-oriented
An Object-Oriented Approach to Schema Integration and Data Mining in Multiple Databases (HD), pp. 294–303.
SACSAC-1997-GoliP #mining #multi
Application of domain vector perfect hash join for multimedia data mining (VNRG, WP), pp. 334–339.
ICLPILPS-1997-Mannila #database #induction #mining
Inductive Databases and Condensed Representations for Data Mining (HM), pp. 21–30.
PODSPODS-1996-BettiniWJ #mining #multi #testing
Testing Complex Temporal Relationships Involving Multiple Granularities and Its Application to Data Mining (CB, XSW, SJ), pp. 68–78.
SIGMODSIGMOD-1996-FukudaMMT #2d #algorithm #mining #using #visualisation
Data Mining Using Two-Dimensional Optimized Accociation Rules: Scheme, Algorithms, and Visualization (TF, YM, SM, TT), pp. 13–23.
SIGMODSIGMOD-1996-Han #mining
Data Mining Techniques (JH), p. 545.
VLDBVLDB-1996-MiningGroup #mining #visualisation
MineSet(tm): A System for High-End Data Mining and Visualization, p. 595.
VLDBVLDB-1996-ShaferAM #classification #mining #named #parallel #scalability
SPRINT: A Scalable Parallel Classifier for Data Mining (JCS, RA, MM), pp. 544–555.
VLDBVLDB-1996-ViverosNR #health #information management #mining
Applying Data Mining Techniques to a Health Insurance Information System (MSV, JPN, MJR), pp. 286–294.
KDDAKDDM-1996-FayyadPS #information management #mining #overview #perspective
From Data Mining to Knowledge Discovery: An Overview (UMF, GPS, PS), pp. 1–34.
KDDAKDDM-1996-HanF #induction #mining
Attribute-Oriented Induction in data Mining (JH, YF), pp. 399–421.
KDDAKDDM-1996-Piatetsky-Shapiro #information management #internet #mining
Data Mining and Knowledge Discovery Internet Resources (GPS), pp. 593–595.
KDDAKDDM-1996-ShenOMZ #mining
Metaqueries for Data Mining (WMS, KO, BGM, CZ), pp. 375–398.
KDDAKDDM-1996-SimoudisLK #deduction #induction #mining #reasoning
Integrating Inductive and Deductive Reasoning for Data Mining (ES, BL, RK), pp. 353–373.
KDDAKDDM-1996-Uthurusamy #challenge #information management #mining
From Data Mining to Knowledge Discovery: Current Challenges and Future Directions (RU), pp. 561–569.
ICMLICML-1996-Mannila #machine learning #mining
Data Mining and Machine Learning (HM), p. 555.
KDDKDD-1996-AgrawalMSSAB #mining
The Quest Data Mining System (RA, MM, JCS, RS, AA, TB), pp. 244–249.
KDDKDD-1996-AgrawalS #database #mining #relational
Developing Tightly-Coupled Data Mining Applications on a Relational Database System (RA, KS), pp. 287–290.
KDDKDD-1996-Fahner #interactive #mining
Data Mining with Sparse and Simplified Interaction Selection (GF), pp. 359–362.
KDDKDD-1996-FawcettP #effectiveness #machine learning #mining #profiling
Combining Data Mining and Machine Learning for Effective User Profiling (TF, FJP), pp. 8–13.
KDDKDD-1996-FayyadPS #framework #information management #mining #towards
Knowledge Discovery and Data Mining: Towards a Unifying Framework (UMF, GPS, PS), pp. 82–88.
KDDKDD-1996-FlockhartR #approach #mining #search-based
A Genetic Algorithm-Based Approach to Data Mining (IWF, NJR), pp. 299–302.
KDDKDD-1996-FultonKSW #induction #interactive #mining #towards
Local Induction of Decision Trees: Towards Interactive Data Mining (TF, SK, SS, DLW), pp. 14–19.
KDDKDD-1996-GrossmanBNP #mining #optimisation
Data Mining and Tree-Based Optimization (RLG, HB, DN, HVP), pp. 323–326.
KDDKDD-1996-JohnL #mining
Static Versus Dynamic Sampling for Data Mining (GHJ, PL), pp. 367–370.
KDDKDD-1996-KontkanenMT #finite #mining #predict
Predictive Data Mining with Finite Mixtures (PK, PM, HT), pp. 176–182.
KDDKDD-1996-Piatetsky-ShapiroBKKS #industrial #information management #mining #overview
An Overview of Issues in Developing Industrial Data Mining and Knowledge Discovery Applications (GPS, RJB, TK, WK, ES), pp. 89–95.
KDDKDD-1996-ProvanS #case study #mining
Data Mining and Model Simplicity: A Case Study in Diagnosis (GMP, MS), pp. 57–62.
KDDKDD-1996-ShekMMN #distributed #mining #scalability
Scalable Exploratory Data Mining of Distributed Geoscientific Data (ECS, RRM, EM, KWN), pp. 32–37.
KDDKDD-1996-ShenL #generative #mining
Metapattern Generation for Integrated Data Mining (WMS, BL), pp. 152–157.
KDDKDD-1996-StolorzD #detection #mining #named #scalability
Quakefinder: A Scalable Data Mining System for Detecting Earthquakes from Space (PES, CD), pp. 208–213.
KDDKDD-1996-WrobelWSE #mining
Extensibility in Data Mining Systems (SW, DW, ES, WE), pp. 214–219.
SEKESEKE-1996-ChangW #case study #mining
Scientific Data Mining: A Case Study (CYC, JTLW), pp. 100–107.
VLDBVLDB-1995-LuSL #approach #mining #named
NeuroRule: A Connectionist Approach to Data Mining (HL, RS, HL), pp. 478–489.
CIKMCIKM-1995-AnandBH #mining
The Role of Domain Knowledge in Data Mining (SSA, DAB, JGH), pp. 37–43.
CIKMCIKM-1995-ParkCY #mining #parallel #performance
Efficient Parallel and Data Mining for Association Rules (JSP, MSC, PSY), pp. 31–36.
KDDKDD-1995-AgrawalP #mining
Active Data Mining (RA, GP), pp. 3–8.
KDDKDD-1995-FeeldersLZ #case study #evaluation #mining
Data Mining for Loan Evaluation at ABN AMRO: A Case Study (AJF, AJFlL, JWvZ), pp. 106–111.
KDDKDD-1995-HolsheimerKMT #database #mining
A Perspective on Databases and Data Mining (MH, MLK, HM, HT), pp. 150–155.
KDDKDD-1995-SeshadriSW #feature model #mining
Feature Extraction for Massive Data Mining (VS, RS, SMW), pp. 258–262.
KDDKDD-1995-StolorzNMMSSYNCMF #dataset #mining #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.
VLDBVLDB-1994-NgH #clustering #effectiveness #mining #performance
Efficient and Effective Clustering Methods for Spatial Data Mining (RTN, JH), pp. 144–155.
KDDKDD-1994-HolsheimerK #architecture #mining
Architectural Support for Data Mining (MH, MLK), pp. 217–228.
CIKMCIKM-1993-CrompC #image #mining #multi
Data Mining of Multi-dimensional Remotely Sensed Images (RFC, WJC), pp. 471–480.
ICMLICML-1993-RaoVF #mining
Data Mining of Subjective Agricultural Data (RBR, TBV, TWF), pp. 244–251.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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