BibSLEIGH — Proceedings of the 12th International Conference on Knowledge Discovery and Data Mining

Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios Gunopulos
Proceedings of the 12th International Conference on Knowledge Discovery and Data Mining
KDD, 2006.

KER

@proceedings{KDD-2006,
	address       = "Philadelphia, Pennsylvania, USA",
	editor        = "Tina Eliassi-Rad and Lyle H. Ungar and Mark Craven and Dimitrios Gunopulos",
	isbn          = "1-59593-339-5",
	publisher     = "{ACM}",
	title         = "{Proceedings of the 12th International Conference on Knowledge Discovery and Data Mining}",
	year          = 2006,
}

Contents (126 items)

KDD-2006-Stankovic #network #self: Self-Organizing wireless sensor networks in action (JAS), p. 1.
KDD-2006-Moore #algorithm #statistics: New cached-sufficient statistics algorithms for quickly answering statistical questions (AM), p. 2.
KDD-2006-Agrawal: Next frontier (RA), p. 3.
KDD-2006-AchtertBKKZ #clustering #correlation #modelling: Deriving quantitative models for correlation clusters (EA, CB, HPK, PK, AZ), pp. 4–13.
KDD-2006-AgarwalCA #learning #rank: Learning to rank networked entities (AA, SC, SA), pp. 14–23.
KDD-2006-AgarwalMPVZ #approximate #performance #statistics: Spatial scan statistics: approximations and performance study (DA, AM, JMP, SV, ZZ), pp. 24–33.
KDD-2006-AnagnostopoulosVHKY #segmentation: Global distance-based segmentation of trajectories (AA, MV, MH, EJK, PSY), pp. 34–43.
KDD-2006-BackstromHKL #evolution #network #scalability #social: Group formation in large social networks: membership, growth, and evolution (LB, DPH, JMK, XL), pp. 44–54.
KDD-2006-BarbaraDR #detection #statistics #testing #using: Detecting outliers using transduction and statistical testing (DB, CD, JPR), pp. 55–64.
KDD-2006-BohmFPP #clustering #robust: Robust information-theoretic clustering (CB, CF, JYP, CP), pp. 65–75.
KDD-2006-BrickellS #performance: Efficient anonymity-preserving data collection (JB, VS), pp. 76–85.
KDD-2006-BuehrerPG #mining: Out-of-core frequent pattern mining on a commodity PC (GB, SP, AG), pp. 86–95.
KDD-2006-CaldersGJ #mining #set: Mining rank-correlated sets of numerical attributes (TC, BG, SJ), pp. 96–105.
KDD-2006-ChenHLN #interactive #named #network: NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs (JC, WH, MLL, SKN), pp. 106–115.
KDD-2006-DavisD #community #rank #web: Estimating the global pagerank of web communities (JVD, ISD), pp. 116–125.
KDD-2006-DingLPP #clustering #matrix #orthogonal: Orthogonal nonnegative matrix t-factorizations for clustering (CHQD, TL, WP, HP), pp. 126–135.
KDD-2006-FanMY #framework #performance #random #summary: A general framework for accurate and fast regression by data summarization in random decision trees (WF, JM, PSY), pp. 136–146.
KDD-2006-FanD #bias #classification #framework #performance #testing: Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.
KDD-2006-Forman #classification #fault #roadmap: Quantifying trends accurately despite classifier error and class imbalance (GF), pp. 157–166.
KDD-2006-GionisMMT #data mining #mining: Assessing data mining results via swap randomization (AG, HM, TM, PT), pp. 167–176.
KDD-2006-HashimotoAUKM #mining #order #performance #probability: A new efficient probabilistic model for mining labeled ordered trees (KH, KFAK, NU, MK, HM), pp. 177–186.
KDD-2006-HoiLC #classification #kernel #learning: Learning the unified kernel machines for classification (SCHH, MRL, EYC), pp. 187–196.
KDD-2006-HorvathRW #graph #mining: Frequent subgraph mining in outerplanar graphs (TH, JR, SW), pp. 197–206.
KDD-2006-IhlerHS #adaptation #detection #process: Adaptive event detection with time-varying poisson processes (ATI, JH, PS), pp. 207–216.
KDD-2006-Joachims #linear: Training linear SVMs in linear time (TJ), pp. 217–226.
KDD-2006-KeCN #approach #correlation #mining #using: Mining quantitative correlated patterns using an information-theoretic approach (YK, JC, WN), pp. 227–236.
KDD-2006-KnobbeH #performance: Maximally informative k-itemsets and their efficient discovery (AJK, EKYH), pp. 237–244.
KDD-2006-KorenNV #network #proximity: Measuring and extracting proximity in networks (YK, SCN, CV), pp. 245–255.
KDD-2006-KumarPT #segmentation #topic: Hierarchical topic segmentation of websites (RK, KP, AT), pp. 257–266.
KDD-2006-LateckiSL: New EM derived from Kullback-Leibler divergence (LJL, MS, RL), pp. 267–276.
KDD-2006-LeFevreDR: Workload-aware anonymization (KL, DJD, RR), pp. 277–286.
KDD-2006-LiHC #random: Very sparse random projections (PL, TH, KWC), pp. 287–296.
KDD-2006-LiuZBX #analysis #using: Rule interestingness analysis using OLAP operations (BL, KZ, JB, WX), pp. 297–306.
KDD-2006-LoekitoB #diagrams #mining #performance #using: Fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams (EL, JB), pp. 307–316.
KDD-2006-LongWZY #graph #learning: Unsupervised learning on k-partite graphs (BL, XW, Z(Z, PSY), pp. 317–326.
KDD-2006-MahoneyMD: Tensor-CUR decompositions for tensor-based data (MWM, MM, PD), pp. 327–336.
KDD-2006-MeiXCHZ #analysis #generative #semantics: Generating semantic annotations for frequent patterns with context analysis (QM, DX, HC, JH, CZ), pp. 337–346.
KDD-2006-MielikainenTT: Aggregating time partitions (TM, ET, PT), pp. 347–356.
KDD-2006-RattiganMJ #approximate #network #performance #using: Using structure indices for efficient approximation of network properties (MJR, MEM, DJ), pp. 357–366.
KDD-2006-RosalesF #learning #linear #metric #programming: Learning sparse metrics via linear programming (RR, GF), pp. 367–373.
KDD-2006-SunTF #analysis #graph: Beyond streams and graphs: dynamic tensor analysis (JS, DT, CF), pp. 374–383.
KDD-2006-TangZL #classification #data-driven #semantics #taxonomy: Acclimatizing taxonomic semantics for hierarchical content classification from semantics to data-driven taxonomy (LT, JZ, HL), pp. 384–393.
KDD-2006-TaoXZ #database #metric #mining #scalability: Mining distance-based outliers from large databases in any metric space (YT, XX, SZ), pp. 394–403.
KDD-2006-TongF #performance #problem: Center-piece subgraphs: problem definition and fast solutions (HT, CF), pp. 404–413.
KDD-2006-WangF: Anonymizing sequential releases (KW, BCMF), pp. 414–423.
KDD-2006-WangM #roadmap #topic: Topics over time: a non-Markov continuous-time model of topical trends (XW, AM), pp. 424–433.
KDD-2006-Webb: Discovering significant rules (GIW), pp. 434–443.
KDD-2006-XinCYH: Extracting redundancy-aware top-k patterns (DX, HC, XY, JH), pp. 444–453.
KDD-2006-YeW #analysis: Regularized discriminant analysis for high dimensional, low sample size data (JY, TW), pp. 454–463.
KDD-2006-YuYTKW #analysis #component #probability: Supervised probabilistic principal component analysis (SY, KY, VT, HPK, MW), pp. 464–473.
KDD-2006-ZhangL #classification #string: Extracting key-substring-group features for text classification (DZ, WSL), pp. 474–483.
KDD-2006-ZhaoLBM #detection #evolution: Event detection from evolution of click-through data (QZ, TYL, SSB, WYM), pp. 484–493.
KDD-2006-ZhuNWZM #detection #web: Simultaneous record detection and attribute labeling in web data extraction (JZ, ZN, JRW, BZ, WYM), pp. 494–503.
KDD-2006-AbeZL #detection #learning: Outlier detection by active learning (NA, BZ, JL), pp. 504–509.
KDD-2006-AggarwalPZ #data mining #mining #on the #privacy: On privacy preservation against adversarial data mining (CCA, JP, BZ), pp. 510–516.
KDD-2006-ArunasalamC #classification #named #top-down: CCCS: a top-down associative classifier for imbalanced class distribution (BA, SC), pp. 517–522.
KDD-2006-Berger-WolfS #analysis #framework #network #social: A framework for analysis of dynamic social networks (TYBW, JS), pp. 523–528.
KDD-2006-BhattacharyaGL: Query-time entity resolution (IB, LG, LL), pp. 529–534.
KDD-2006-BucilaCN: Model compression (CB, RC, ANM), pp. 535–541.
KDD-2006-BurkeMWB #classification #collaboration #detection #recommendation: Classification features for attack detection in collaborative recommender systems (RDB, BM, CW, RB), pp. 542–547.
KDD-2006-CarvalhoC #feature model #learning #online #performance: Single-pass online learning: performance, voting schemes and online feature selection (VRC, WWC), pp. 548–553.
KDD-2006-ChakrabartiKT #clustering: Evolutionary clustering (DC, RK, AT), pp. 554–560.
KDD-2006-GionisMPU #algorithm #order: Algorithms for discovering bucket orders from data (AG, HM, KP, AU), pp. 561–566.
KDD-2006-GuoV #mining #multi #relational #validation: Mining relational data through correlation-based multiple view validation (HG, HLV), pp. 567–573.
KDD-2006-IwataSY #recommendation: Recommendation method for extending subscription periods (TI, KS, TY), pp. 574–579.
KDD-2006-JankSW #functional #modelling #online #realtime: Dynamic, real-time forecasting of online auctions via functional models (WJ, GS, SW), pp. 580–585.
KDD-2006-Jaroszewicz #polynomial: Polynomial association rules with applications to logistic regression (SJ), pp. 586–591.
KDD-2006-JiangG #data type #mining #named: CFI-Stream: mining closed frequent itemsets in data streams (NJ, LG), pp. 592–597.
KDD-2006-KonigB #categorisation: Reducing the human overhead in text categorization (ACK, EB), pp. 598–603.
KDD-2006-KumarRHP #algorithm: Algorithms for storytelling (DK, NR, RFH, MP), pp. 604–610.
KDD-2006-KumarNT #evolution #network #online #social: Structure and evolution of online social networks (RK, JN, AT), pp. 611–617.
KDD-2006-LaurLM #encryption: Cryptographically private support vector machines (SL, HL, TM), pp. 618–624.
KDD-2006-LauwLW #bias #statistics: Bias and controversy: beyond the statistical deviation (HWL, EPL, KW), pp. 625–630.
KDD-2006-LeskovecF #graph #scalability: Sampling from large graphs (JL, CF), pp. 631–636.
KDD-2006-LiuZWMP #clustering #difference #order #set: Clustering pair-wise dissimilarity data into partially ordered sets (JL, QZ, WW, LM, JP), pp. 637–642.
KDD-2006-ManiyarN #algorithm #data mining #mining #using #visual notation #visualisation: Visual data mining using principled projection algorithms and information visualization techniques (DMM, ITN), pp. 643–648.
KDD-2006-MeiZ #mining: A mixture model for contextual text mining (QM, CZ), pp. 649–655.
KDD-2006-MeruguRP #approach #estimation #multi: A new multi-view regression approach with an application to customer wallet estimation (SM, SR, CP), pp. 656–661.
KDD-2006-MessaoudBR #analysis #data transformation #multi #performance: Efficient multidimensional data representations based on multiple correspondence analysis (RBM, OB, SLR), pp. 662–667.
KDD-2006-Morchen #algorithm #mining: Algorithms for time series knowledge mining (FM), pp. 668–673.
KDD-2006-NathBM #approach #classification #clustering #scalability #using: Clustering based large margin classification: a scalable approach using SOCP formulation (JSN, CB, MNM), pp. 674–679.
KDD-2006-NewmanCS #modelling #statistics #topic: Statistical entity-topic models (DN, CC, PS), pp. 680–686.
KDD-2006-PalatinLSW #grid #mining: Mining for misconfigured machines in grid systems (NP, AL, AS, RW), pp. 687–692.
KDD-2006-PanGBXTF #automation #image #mining: Automatic mining of fruit fly embryo images (JYP, AGRB, EPX, AJMT, CF), pp. 693–698.
KDD-2006-ParkPMGD #recommendation #robust: Naïve filterbots for robust cold-start recommendations (STP, DP, OM, NG, DD), pp. 699–705.
KDD-2006-SpiliopoulouNTS #clustering #modelling #monitoring #named: MONIC: modeling and monitoring cluster transitions (MS, IN, YT, RS), pp. 706–711.
KDD-2006-SuchanekIW #analysis #documentation #statistics #web: Combining linguistic and statistical analysis to extract relations from web documents (FMS, GI, GW), pp. 712–717.
KDD-2006-TanSZ #mining: Mining long-term search history to improve search accuracy (BT, XS, CZ), pp. 718–723.
KDD-2006-TsangKK #feature model #kernel #performance #set: Efficient kernel feature extraction for massive data sets (IWT, AK, JTK), pp. 724–729.
KDD-2006-WangP #modelling #probability #using: Summarizing itemset patterns using probabilistic models (CW, SP), pp. 730–735.
KDD-2006-WangYPYY #concept #data type #mining: Suppressing model overfitting in mining concept-drifting data streams (HW, JY, JP, PSY, JXY), pp. 736–741.
KDD-2006-WedigM #analysis #personalisation #query #scalability: A large-scale analysis of query logs for assessing personalization opportunities (SW, OM), pp. 742–747.
KDD-2006-WeiK #classification: Semi-supervised time series classification (LW, EJK), pp. 748–753.
KDD-2006-WongLFW #privacy: (alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing (RCWW, JL, AWCF, KW), pp. 754–759.
KDD-2006-WuCCH #approximate #incremental #matrix: Incremental approximate matrix factorization for speeding up support vector machines (GW, EYC, YKC, CJH), pp. 760–766.
KDD-2006-AbeZL06a #detection: Outlier detection by sampling with accuracy guarantees (MW, CJ), pp. 767–772.
KDD-2006-XinSMH #feedback #interactive: Discovering interesting patterns through user’s interactive feedback (DX, XS, QM, JH), pp. 773–778.
KDD-2006-XiongWC #clustering #metric #perspective #validation: K-means clustering versus validation measures: a data distribution perspective (HX, JW, JC), pp. 779–784.
KDD-2006-XuWPWSF #using: Utility-based anonymization using local recoding (JX, WW, JP, XW, BS, AWCF), pp. 785–790.
KDD-2006-YooHS #clustering #graph #integration #refinement #representation #semantics: Integration of semantic-based bipartite graph representation and mutual refinement strategy for biomedical literature clustering (IY, XH, IYS), pp. 791–796.
KDD-2006-ZengWZK #clique #database #graph #scalability: Coherent closed quasi-clique discovery from large dense graph databases (ZZ, JW, LZ, GK), pp. 797–802.
KDD-2006-ZhangHL #mining: Mining progressive confident rules (MZ, WH, MLL), pp. 803–808.
KDD-2006-ZhangCFM #detection #recommendation: Attack detection in time series for recommender systems (SZ, AC, JF, FM), pp. 809–814.
KDD-2006-ZhangCWZ #clustering #concept #identification: Identifying bridging rules between conceptual clusters (SZ, FC, XW, CZ), pp. 815–820.
KDD-2006-ZhangPD #categorisation #graph #linear #modelling #predict: Linear prediction models with graph regularization for web-page categorization (TZ, AP, BD), pp. 821–826.
KDD-2006-ZhaoZR #framework #mining #named: BLOSOM: a framework for mining arbitrary boolean expressions (LZ, MJZ, NR), pp. 827–832.
KDD-2006-Jonas: Introducing perpetual analytics (JJ), p. 833.
KDD-2006-Kahn #problem #statistics: Capital One’s statistical problems: our top ten list (WK), p. 834.
KDD-2006-McCallum #data mining #information management #mining: Information extraction, data mining and joint inference (AM), p. 835.
KDD-2006-Cavaretta #challenge #data mining #mining: Data mining challenges in the automotive domain (MC), p. 836.
KDD-2006-BiPOKFSR #classification #detection #symmetry: Computer aided detection via asymmetric cascade of sparse hyperplane classifiers (JB, SP, KO, TK, GF, MS, RBR), pp. 837–844.
KDD-2006-CastanoMTGDCCD #classification #detection: Onboard classifiers for science event detection on a remote sensing spacecraft (RC, DM, NT, RG, TD, BC, SAC, AD), pp. 845–851.
KDD-2006-FormanKS #mining: Pragmatic text mining: minimizing human effort to quantify many issues in call logs (GF, EK, JS), pp. 852–861.
KDD-2006-HettichP #lessons learnt #mining: Mining for proposal reviewers: lessons learned at the national science foundation (SH, MJP), pp. 862–871.
KDD-2006-LiuCHY #analysis #dependence #detection #graph #named: GPLAG: detection of software plagiarism by program dependence graph analysis (CL, CC, JH, PSY), pp. 872–881.
KDD-2006-MorchenMU #generative #modelling #music #statistics: Understandable models Of music collections based on exhaustive feature generation with temporal statistics (FM, IM, AU), pp. 882–891.
KDD-2006-ZhaoLBX #data mining #identification #mining: Opportunity map: identifying causes of failure — a deployed data mining system (KZ, BL, JB, WX), pp. 892–901.
KDD-2006-AgichteinZ #behaviour #identification #mining #web: Identifying “best bet” web search results by mining past user behavior (EA, ZZ), pp. 902–908.
KDD-2006-CaruanaEMRSFHK #mining #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-EtienneWZ #component #framework #information management: A component-based framework for knowledge discovery in bioinformatics (JE, BW, LZ), pp. 916–921.
KDD-2006-GaoGEJ #clustering: Discovering significant OPSM subspace clusters in massive gene expression data (BJG, OLG, ME, SJMJ), pp. 922–928.
KDD-2006-LingSBM #development #mining: Maximum profit mining and its application in software development (CXL, VSS, TFWB, NHM), pp. 929–934.
KDD-2006-MierswaWKSE #agile #data mining #mining #named #prototype: YALE: rapid prototyping for complex data mining tasks (IM, MW, RK, MS, TE), pp. 935–940.
KDD-2006-VirdhagriswaranD #detection: Camouflaged fraud detection in domains with complex relationships (SV, GD), pp. 941–947.
KDD-2006-YanB #classification #optimisation #ranking: Beyond classification and ranking: constrained optimization of the ROI (LY, PB), pp. 948–953.
KDD-2006-Piatetsky-ShapiroGDFGZ #challenge #data mining #mining #question: Is there a grand challenge or X-prize for data mining? (GPS, RG, CD, RF, LG, MJZ), pp. 954–956.

Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios GunopulosProceedings of the 12th International Conference on Knowledge Discovery and Data MiningKDD, 2006.

Contents (126 items)

Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios Gunopulos
Proceedings of the 12th International Conference on Knowledge Discovery and Data Mining
KDD, 2006.