Introduction

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  Welcome Message from the Conference Chairs.
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  Welcome to ICDM 2005.
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  Conference Organization.
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  Steering Committee.
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  Program Committee.
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  Non-PC Reviewers.
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  Invited Talks.
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  Tutorials.
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  Workshops.
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  Panel Session.

Regular Papers

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  Alan S. Abrahams, Adrian Becker, Daniel Fleder, Ian C. MacMillan: Handling Generalized Cost Functions in the Partitioning Optimization Problem through Sequential Binary Programming. 3-9
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  Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger: Online Hierarchical Clustering in a Data Warehouse Environment. 10-17
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  Manu Aery, Sharma Chakravarthy: eMailSift: Email Classification Based on Structure and Content. 18-25
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  Deepak K. Agarwal: An Empirical Bayes Approach to Detect Anomalies in Dynamic Multidimensional Arrays. 26-33
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  Costin Barbu, Raja Tanveer Iqbal, Jing Peng: Classifier Fusion Using Shared Sampling Distribution for Boosting. 34-41
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  Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, David D. Lewis, Abdur Chowdhury, Aleksander Kolcz: Improving Automatic Query Classification via Semi-Supervised Learning. 42-49
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  Arnab Bhattacharya, Vebjorn Ljosa, Jia-Yu Pan, Mark R. Verardo, Hyung-Jeong Yang, Christos Faloutsos, Ambuj K. Singh: ViVo: Visual Vocabulary Construction for Mining Biomedical Images. 50-57
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  Mikhail Bilenko, Sugato Basu, Mehran Sahami: Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping. 58-65
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  Julien Blanchard, Fabrice Guillet, Régis Gras, Henri Briand: Using Information-Theoretic Measures to Assess Association Rule Interestingness. 66-73
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  Karsten M. Borgwardt, Hans-Peter Kriegel: Shortest-Path Kernels on Graphs. 74-81
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  Huiping Cao, Nikos Mamoulis, David W. Cheung: Mining Frequent Spatio-Temporal Sequential Patterns. 82-89
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  Philip K. Chan, Matthew V. Mahoney: Modeling Multiple Time Series for Anomaly Detection. 90-97
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  Varun Chandola, Vipin Kumar: Summarization - Compressing Data into an Informative Representation. 98-105
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  Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen: Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values. 106-113
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  Jason R. Chen: Making Subsequence Time Series Clustering Meaningful. 114-121
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  Anne Denton: Kernel-Density-Based Clustering of Time Series Subsequences Using a Continuous Random-Walk Noise Model. 122-129
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  Magdalini Eirinaki, Michalis Vazirgiannis: Usage-Based PageRank for Web Personalization. 130-137
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  Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagarmid: WARP: Time Warping for Periodicity Detection. 138-145
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  Mohammad El-Hajj, Osmar R. Zaïane, Paul Nalos: Bifold Constraint-Based Mining by Simultaneous Monotone and Anti-Monotone Checking. 146-153
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  Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Yu, Kevin Drummey: Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches. 154-161
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  Frédéric Flouvat, Fabien De Marchi, Jean-Marc Petit: A Thorough Experimental Study of Datasets for Frequent Itemsets. 162-169
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  Shohei Hido, Hiroyuki Kawano: AMIOT: Induced Ordered Tree Mining in Tree-Structured Databases. 170-177
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  Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-Peter Kriegel: Hierarchy-Regularized Latent Semantic Indexing. 178-185
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  Koji Iwanuma, Ryuichi Ishihara, Yo Takano, Hidetomo Nabeshima: Extracting Frequent Subsequences from a Single Long Data Sequence: A Novel Anti-Monotonic Measure and a Simple On-Line Algorithm. 186-193
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  Xiaonan Ji, James Bailey, Guozhu Dong: Mining Minimal Distinguishing Subsequence Patterns with Gap Constraints. 194-201
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  Liangxiao Jiang, Harry Zhang: Learning Instance Greedily Cloning Naive Bayes for Ranking. 202-209
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  Ruoming Jin, Gagan Agrawal: An Algorithm for In-Core Frequent Itemset Mining on Streaming Data. 210-217
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  Alexandros Kalousis, Julien Prados, Melanie Hilario: Stability of Feature Selection Algorithms. 218-225
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  Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu: HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence. 226-233
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  Effrosini Kokiopoulou, Yousef Saad: Orthogonal Neighborhood Preserving Projections. 234-241
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  Tamara G. Kolda, Brett W. Bader, Joseph P. Kenny: Higher-Order Web Link Analysis Using Multilinear Algebra. 242-249
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  Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Sebastian H. R. Wurst: A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data. 250-257
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  Hans-Peter Kriegel, Peer Kröger, Alexey Pryakhin, Matthias Schubert: Effective and Efficient Distributed Model-Based Clustering. 258-265
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  Daesu Lee, Wonsuk Lee: Finding Maximal Frequent Itemsets over Online Data Streams Adaptively. 266-273
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  Carson Kai-Sang Leung, Quamrul I. Khan, Tariqul Hoque: CanTree: A Tree Structure for Efficient Incremental Mining of Frequent Patterns. 274-281
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  Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu: Combining Multiple Clusterings by Soft Correspondence. 282-289
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  Anna M. Manning, David J. Haglin: A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment. 290-297
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  Keith Marsolo, Srinivasan Parthasarathy: Alternate Representation of Distance Matrices for Characterization of Protein Structure. 298-305
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  Shawn Martin: Training Support Vector Machines Using Gilbert's Algorithm. 306-313
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  Steven Minton, Claude Nanjo, Craig A. Knoblock, Martin Michalowski, Matthew Michelson: A Heterogeneous Field Matching Method for Record Linkage. 314-321
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  Jennifer Neville, David Jensen: Leveraging Relational Autocorrelation with Latent Group Models. 322-329
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  Thomas Takeo Osugi, Kun Deng, Stephen D. Scott: Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning. 330-337
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  Feng Pan, Wei Wang, Anthony K. H. Tung, Jiong Yang: Finding Representative Set from Massive Data. 338-345
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  Spiros Papadimitriou, Aristides Gionis, Panayiotis Tsaparas, Risto A. Väisänen, Heikki Mannila, Christos Faloutsos: Parameter-Free Spatial Data Mining Using MDL. 346-353
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  Panagiotis Papapetrou, George Kollios, Stan Sclaroff, Dimitrios Gunopulos: Discovering Frequent Arrangements of Temporal Intervals. 354-361
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  Marcelino Pereira dos Santos Silva, Gilberto Câmara, Ricardo Cartaxo Modesto de Souza, Dalton M. Valeriano, Maria Isabel Sobral Escada: Mining Patterns of Change in Remote Sensing Image Databases. 362-369
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  Saharon Rosset, Claudia Perlich, Bianca Zadrozny: Ranking-Based Evaluation of Regression Models. 370-377
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  Lars Schmidt-Thieme: Compound Classification Models for Recommender Systems. 378-385
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  Ted E. Senator: Multi-Stage Classification. 386-393
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  Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong: Learning Functional Dependency Networks Based on Genetic Programming. 394-401
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  Michael Steinbach, Vipin Kumar: Generalizing the Notion of Confidence. 402-409
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  Jonathan Stoeckel, Glenn Fung: SVM Feature Selection for Classification of SPECT Images of Alzheimer's Disease Using Spatial Information. 410-417
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  Jimeng Sun, Huiming Qu, Deepayan Chakrabarti, Christos Faloutsos: Neighborhood Formation and Anomaly Detection in Bipartite Graphs. 418-425
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  Xingzhi Sun, Philip S. Yu: A Border-Based Approach for Hiding Sensitive Frequent Itemsets. 426-433
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  Zoltán Szamonek, Csaba Szepesvári: X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is Unknown. 434-441
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  Raz Tamir: A Random Walk through Human Associations. 442-449
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  Dacheng Tao, Xuelong Li, Weiming Hu, Stephen J. Maybank, Xindong Wu: Supervised Tensor Learning. 450-457
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  Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. Lochovsky: A Bernoulli Relational Model for Nonlinear Embedding. 458-465
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  Ke Wang, Benjamin C. M. Fung, Philip S. Yu: Template-Based Privacy Preservation in Classification Problems. 466-473
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  Peng Wang, Haixun Wang, Xiaochen Wu, Wei Wang, Baile Shi: On Reducing Classifier Granularity in Mining Concept-Drifting Data Streams. 474-481
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  Yongge Wang, Xintao Wu: Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. 482-489
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  Li Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto: Atomic Wedgie: Efficient Query Filtering for Streaming Times Series. 490-497
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  Oksana Yakhnenko, Adrian Silvescu, Vasant Honavar: Discriminatively Trained Markov Model for Sequence Classification. 498-505
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  Jie Yin, Qiang Yang: Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering. 506-513
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  Peng Zhang, Norbert Riedel: Discriminant Analysis: A Unified Approach. 514-521
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  Yi Zhang, W. Nick Street, Samuel Burer: Sharing Classifiers among Ensembles from Related Problem Domains. 522-529
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  Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xiao: A Visual Data Mining Framework for Convenient Identification of Useful Knowledge. 530-537
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  Dong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zheng Chen, Ying Chen: Efficient Text Classification by Weighted Proximal SVM. 538-545

Short Papers

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  Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes. 549-552
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  Foto N. Afrati, Gautam Das, Aristides Gionis, Heikki Mannila, Taneli Mielikäinen, Panayiotis Tsaparas: Mining Chains of Relations. 553-556
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  Fabio Aiolli: A Preference Model for Structured Supervised Learning Tasks. 557-560
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  Maurizio Atzori, Francesco Bonchi, Fosca Giannotti, Dino Pedreschi: Blocking Anonymity Threats Raised by Frequent Itemset Mining. 561-564
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  Abraham Bagherjeiran, Christoph F. Eick, Chun-Sheng Chen, Ricardo Vilalta: Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience. 565-568
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  Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao: Semi-Supervised Mixture of Kernels via LPBoost Methods. 569-572
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  Haiyun Bian, Raj Bhatnagar: A Levelwise Search Algorithm for Interesting Subspace Clusters. 573-576
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  Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams: Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems. 577-580
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  Richard Butterworth, Gregory Piatetsky-Shapiro, Dan A. Simovici: On Feature Selection through Clustering. 581-584
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  Gong Chen, Xindong Wu, Xingquan Zhu: Sequential Pattern Mining in Multiple Streams. 585-588
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  Keke Chen, Ling Liu: Privacy Preserving Data Classification with Rotation Perturbation. 589-592
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  Yixin Chen, Henry L. Bart Jr., Shuqing Huang, Huimin Chen: A Computational Framework for Taxonomic Research: Diagnosing Body Shape within Fish Species Complexes. 593-596
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  Frans Coenen, Paul H. Leng: Obtaining Best Parameter Values for Accurate Classification. 597-600
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  Federico Di Palma, Giuseppe De Nicolao, Guido Miraglia, Oliver M. Donzelli: Process Diagnosis via Electrical-Wafer-Sorting Maps Classification. 601-604
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  Wei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu: An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias. 605-608
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  Johannes Fischer, Volker Heun, Stefan Kramer: Fast Frequent String Mining Using Suffix Arrays. 609-612
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  Ada Wai-Chee Fu, Raymond Chi-Wing Wong, Ke Wang: Privacy-Preserving Frequent Pattern Mining across Private Databases. 613-616
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  Jie Gao, Jörg Denzinger, Robert C. James: CoLe: A Cooperative Data Mining Approach and Its Application to Early Diabetes Detection. 617-620
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  Like Gao, Xiaoyang Sean Wang: Feature Selection for Building Cost-Effective Data Stream Classifiers. 621-624
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  Thomas George, Srujana Merugu: A Scalable Collaborative Filtering Framework Based on Co-Clustering. 625-628
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  Shantanu Godbole, Ganesh Ramakrishnan, Sunita Sarawagi: Text Classification with Evolving Label-Sets. 629-632
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  Ningthoujam Gourakishwar Singh, Sanasam Ranbir Singh, Anjana K. Mahanta: CloseMiner: Discovering Frequent Closed Itemsets Using Frequent Closed Tidsets. 633-636
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  Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, Michalis Vazirgiannis, Carlotta Domeniconi: A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria. 637-640
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  Kirsten Hildrum, Philip S. Yu: Focused Community Discovery. 641-644
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  Ayça Azgin Hintoglu, Ali Inan, Yücel Saygin, Mehmet Keskinöz: Suppressing Data Sets to Prevent Discovery of Association Rules. 645-648
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  Han-Shen Huang, Bou-Ho Yang, Chun-Nan Hsu: Triple Jump Acceleration for the EM Algorithm. 649-652
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  Jin Huang, Charles X. Ling: Partial Ensemble Classifiers Selection for Better Ranking. 653-656
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  Tsuyoshi Idé: Pairwise Symmetry Decomposition Method for Generalized Covariance Analysis. 657-660
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  Vandana Pursnani Janeja, Vijayalakshmi Atluri: FS³: A Random Walk Based Free-Form Spatial Scan Statistic for Anomalous Window Detection. 661-664
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  Xing Jiang, Ah-Hwee Tan: Mining Ontological Knowledge from Domain-Specific Text Documents. 665-668
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  Yuelong Jiang, Ke Wang, Alexander Tuzhilin, Ada Wai-Chee Fu: Mining Patterns That Respond to Actions. 669-672
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  Toshihiro Kamishima, Hideto Kazawa, Shotaro Akaho: Supervised Ordering - An Empirical Survey. 673-676
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  Ning Kang, Carlotta Domeniconi, Daniel Barbará: Categorization and Keyword Identification of Unlabeled Documents. 677-680
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  Ismo Kärkkäinen, Pasi Fränti: Gradual Model Generator for Single-Pass Clustering. 681-684
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  Paul Komarek, Andrew W. Moore: Making Logistic Regression a Core Data Mining Tool with TR-IRLS. 685-688
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  Hans-Peter Kriegel, Martin Pfeifle: Hierarchical Density-Based Clustering of Uncertain Data. 689-692
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  Nimit Kumar, Krishna Kummamuru, Deepa Paranjpe: Semi-Supervised Clustering with Metric Learning Using Relative Comparisons. 693-696
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  Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agrawal: On Learning Asymmetric Dissimilarity Measures. 697-700
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  Longin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakämper, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh: Partial Elastic Matching of Time Series. 701-704
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  In-Yee Lee, Jan-Ming Ho, Ming-Syan Chen: CLUGO: A Clustering Algorithm for Automated Functional Annotations Based on Gene Ontology. 705-708
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  Daniel Lemire, Martin Brooks, Yuhong Yan: An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation. 709-712
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  Loïck Lhote, François Rioult, Arnaud Soulet: Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases. 713-716
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  Charles X. Ling, Shengli Sheng, Tilmann F. W. Bruckhaus, Nazim H. Madhavji: Predicting Software Escalations with Maximum ROI. 717-720
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  Jinze Liu, Susan Paulsen, Wei Wang, Andrew B. Nobel, Jan Prins: Mining Approximate Frequent Itemsets from Noisy Data. 721-724
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  Ning Liu, Benyu Zhang, Jun Yan, Zheng Chen, Wenyin Liu, Fengshan Bai, Leefeng Chien: Text Representation: From Vector to Tensor. 725-728
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  Elio Lozano, Edgar Acuña: Parallel Algorithms for Distance-Based and Density-Based Outliers. 729-732
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  Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen: Bit Reduction Support Vector Machine. 733-736
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  Sandeep Mane, Carson Murray, Shashi Shekhar, Jaideep Srivastava, Anne Pusey: Spatial Clustering of Chimpanzee Locations for Neighborhood Identification. 737-740
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  Bruno Martins, Mário J. Silva: A Graph-Ranking Algorithm for Geo-Referencing Documents. 741-744
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  Prem Melville, Foster J. Provost, Raymond J. Mooney: An Expected Utility Approach to Active Feature-Value Acquisition. 745-748
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  Dheerendranath Mundluru, Jayasimha Reddy Katukuri, Saygin Celebi: Automatically Mining Result Records from Search Engine Response Pages. 749-752
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  Jian Pei, Jian Liu, Haixun Wang, Ke Wang, Philip S. Yu, Jianyong Wang: Efficiently Mining Frequent Closed Partial Orders. 753-756
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  Kunal Punera, Joydeep Ghosh: CLUMP: A Scalable and Robust Framework for Structure Discovery. 757-760
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  Martin Scholz: On the Tractability of Rule Discovery from Distributed Data. 761-764
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  Jiazheng Shi, Ashok Samal, David Marx: Face Recognition Using Landmark-Based Bidimensional Regression. 765-768
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  Arno Siebes, Muhammad Subianto, A. J. Feelders: Instability of Classifiers on Categorical Data. 769-772
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  Lisa Singh, Lise Getoor, Louis Licamele: Pruning Social Networks Using Structural Properties and Descriptive Attributes. 773-776
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  Arnaud Soulet, Bruno Crémilleux: Optimizing Constraint-Based Mining by Automatically Relaxing Constraints. 777-780
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  Lei Tang, Huan Liu: Bias Analysis in Text Classification for Highly Skewed Data. 781-784
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  Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda: Efficient Mining of High Branching Factor Attribute Trees. 785-788
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  Chi-Ho Tsang, Sam Kwong, Hanli Wang: Anomaly Intrusion Detection Using Multi-Objective Genetic Fuzzy System and Agent-Based Evolutionary Computation Framework. 789-792
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  Takashi Washio, Yuki Mitsunaga, Hiroshi Motoda: Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering. 793-796
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  Tak-Lam Wong, Wai Lam: Hot Item Mining and Summarization from Multiple Auction Web Sites. 797-800
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  Wensheng Wu, AnHai Doan, Clement T. Yu: Merging Interface Schemas on the Deep Web via Clustering Aggregation. 801-804
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  Kiyoung Yang, Cyrus Shahabi: On the Stationarity of Multivariate Time Series for Correlation-Based Data Analysis. 805-808
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  Sandeep Yaramakala, Dimitris Margaritis: Speculative Markov Blanket Discovery for Optimal Feature Selection. 809-812
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  Jin Soung Yoo, Shashi Shekhar, Mete Celik: A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results. 813-816
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  Kun Zhang, Zujia Xu, Jing Peng, Bill P. Buckles: Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation Trees. 817-820
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  Xiaofeng Zhang, William K. Cheung: Visualizing Global Manifold Based on Distributed Local Data Abstractions. 821-824
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  Yi Zhang, W. Nick Street: Bagging with Adaptive Costs. 825-828
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  Cui Zhu, Hiroyuki Kitagawa, Christos Faloutsos: Example-Based Robust Outlier Detection in High Dimensional Datasets. 829-832
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  Albrecht Zimmermann, Björn Bringmann: CTC - Correlating Tree Patterns for Classification. 833-836

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