Table of Contents

• Steering Committee [doi]
• Invited Talks [doi]
• Conference Organization [doi]
• Workshops [doi]
• Welcome Message from the Conference Chairs [doi]
• Non-PC Reviewers [doi]
• Welcome to ICDM 2005 [doi]
• Tutorials [doi]
• Panel Session [doi]
• Program Committee [doi]
• Handling Generalized Cost Functions in the Partitioning Optimization Problem through Sequential Binary ProgrammingAlan S. Abrahams, Adrian Becker, Daniel Fleder, Ian C. MacMillan. 3-9 [doi]
• Online Hierarchical Clustering in a Data Warehouse EnvironmentElke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger. 10-17 [doi]
• eMailSift: Email Classification Based on Structure and ContentManu Aery, Sharma Chakravarthy. 18-25 [doi]
• An Empirical Bayes Approach to Detect Anomalies in Dynamic Multidimensional ArraysDeepak K. Agarwal. 26-33 [doi]
• Classifier Fusion Using Shared Sampling Distribution for BoostingCostin Barbu, Raja Tanveer Iqbal, Jing Peng. 34-41 [doi]
• Improving Automatic Query Classification via Semi-Supervised LearningSteven M. Beitzel, Eric C. Jensen, Ophir Frieder, David D. Lewis, Abdur Chowdhury, Aleksander Kolcz. 42-49 [doi]
• ViVo: Visual Vocabulary Construction for Mining Biomedical ImagesArnab Bhattacharya, Vebjorn Ljosa, Jia-Yu Pan, Mark R. Verardo, Hyung Jeong Yang, Christos Faloutsos, Ambuj K. Singh. 50-57 [doi]
• Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison ShoppingMikhail Bilenko, Sugato Basu, Mehran Sahami. 58-65 [doi]
• Using Information-Theoretic Measures to Assess Association Rule InterestingnessJulien Blanchard, Fabrice Guillet, Régis Gras, Henri Briand. 66-73 [doi]
• Shortest-Path Kernels on GraphsKarsten M. Borgwardt, Hans-Peter Kriegel. 74-81 [doi]
• Mining Frequent Spatio-Temporal Sequential PatternsHuiping Cao, Nikos Mamoulis, David W. Cheung. 82-89 [doi]
• Modeling Multiple Time Series for Anomaly DetectionPhilip K. Chan, Matthew V. Mahoney. 90-97 [doi]
• Summarization - Compressing Data into an Informative RepresentationVarun Chandola, Vipin Kumar. 98-105 [doi]
• Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute ValuesHung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen. 106-113 [doi]
• Making Subsequence Time Series Clustering MeaningfulJason R. Chen. 114-121 [doi]
• Kernel-Density-Based Clustering of Time Series Subsequences Using a Continuous Random-Walk Noise ModelAnne Denton. 122-129 [doi]
• Usage-Based PageRank for Web PersonalizationMagdalini Eirinaki, Michalis Vazirgiannis. 130-137 [doi]
• WARP: Time Warping for Periodicity DetectionMohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagarmid. 138-145 [doi]
• Bifold Constraint-Based Mining by Simultaneous Monotone and Anti-Monotone CheckingMohammad El-Hajj, Osmar R. Zaïane, Paul Nalos. 146-153 [doi]
• Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree ApproachesWei Fan, Ed Greengrass, Joe McCloskey, Philip S. Yu, Kevin Drummey. 154-161 [doi]
• A Thorough Experimental Study of Datasets for Frequent ItemsetsFrédéric Flouvat, Fabien De Marchi, Jean-Marc Petit. 162-169 [doi]
• AMIOT: Induced Ordered Tree Mining in Tree-Structured DatabasesShohei Hido, Hiroyuki Kawano. 170-177 [doi]
• Hierarchy-Regularized Latent Semantic IndexingYi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-Peter Kriegel. 178-185 [doi]
• Extracting Frequent Subsequences from a Single Long Data Sequence: A Novel Anti-Monotonic Measure and a Simple On-Line AlgorithmKoji Iwanuma, Ryuichi Ishihara, Yo Takano, Hidetomo Nabeshima. 186-193 [doi]
• Mining Minimal Distinguishing Subsequence Patterns with Gap ConstraintsXiaonan Ji, James Bailey, Guozhu Dong. 194-201 [doi]
• Learning Instance Greedily Cloning Naive Bayes for RankingLiangxiao Jiang, Harry Zhang. 202-209 [doi]
• An Algorithm for In-Core Frequent Itemset Mining on Streaming DataRuoming Jin, Gagan Agrawal. 210-217 [doi]
• Stability of Feature Selection AlgorithmsAlexandros Kalousis, Julien Prados, Melanie Hilario. 218-225 [doi]
• HOT SAX: Efficiently Finding the Most Unusual Time Series SubsequenceEamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu. 226-233 [doi]
• Orthogonal Neighborhood Preserving ProjectionsEffrosini Kokiopoulou, Yousef Saad. 234-241 [doi]
• Higher-Order Web Link Analysis Using Multilinear AlgebraTamara G. Kolda, Brett W. Bader, Joseph P. Kenny. 242-249 [doi]
• A Generic Framework for Efficient Subspace Clustering of High-Dimensional DataHans-Peter Kriegel, Peer Kröger, Matthias Renz, Sebastian Wurst. 250-257 [doi]
• Effective and Efficient Distributed Model-Based ClusteringHans-Peter Kriegel, Peer Kröger, Alexey Pryakhin, Matthias Schubert. 258-265 [doi]
• Finding Maximal Frequent Itemsets over Online Data Streams AdaptivelyDaesu Lee, Wonsuk Lee. 266-273 [doi]
• CanTree: A Tree Structure for Efficient Incremental Mining of Frequent PatternsCarson Kai-Sang Leung, Quamrul I. Khan, Tariqul Hoque. 274-281 [doi]
• Combining Multiple Clusterings by Soft CorrespondenceBo Long, Zhongfei (Mark) Zhang, Philip S. Yu. 282-289 [doi]
• A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure AssessmentAnna M. Manning, David J. Haglin. 290-297 [doi]
• Alternate Representation of Distance Matrices for Characterization of Protein StructureKeith Marsolo, Srinivasan Parthasarathy. 298-305 [doi]
• Training Support Vector Machines Using Gilbert s AlgorithmShawn Martin. 306-313 [doi]
• A Heterogeneous Field Matching Method for Record LinkageSteven Minton, Claude Nanjo, Craig A. Knoblock, Martin Michalowski, Matthew Michelson. 314-321 [doi]
• Leveraging Relational Autocorrelation with Latent Group ModelsJennifer Neville, David Jensen. 322-329 [doi]
• Balancing Exploration and Exploitation: A New Algorithm for Active Machine LearningThomas Takeo Osugi, Kun Deng, Stephen D. Scott. 330-337 [doi]
• Finding Representative Set from Massive DataFeng Pan, Wei Wang 0010, Anthony K. H. Tung, Jiong Yang. 338-345 [doi]
• Parameter-Free Spatial Data Mining Using MDLSpiros Papadimitriou, Aristides Gionis, Panayiotis Tsaparas, Risto A. Väisänen, Heikki Mannila, Christos Faloutsos. 346-353 [doi]
• Discovering Frequent Arrangements of Temporal IntervalsPanagiotis Papapetrou, George Kollios, Stan Sclaroff, Dimitrios Gunopulos. 354-361 [doi]
• Mining Patterns of Change in Remote Sensing Image DatabasesMarcelino Pereira dos Santos Silva, Gilberto Câmara, Ricardo Cartaxo Modesto de Souza, Dalton M. Valeriano, Maria Isabel Sobral Escada. 362-369 [doi]
• Ranking-Based Evaluation of Regression ModelsSaharon Rosset, Claudia Perlich, Bianca Zadrozny. 370-377 [doi]
• Compound Classification Models for Recommender SystemsLars Schmidt-Thieme. 378-385 [doi]
• Multi-Stage ClassificationTed E. Senator. 386-393 [doi]
• Learning Functional Dependency Networks Based on Genetic ProgrammingWing-Ho Shum, Kwong-Sak Leung, Man Leung Wong. 394-401 [doi]
• Generalizing the Notion of ConfidenceMichael Steinbach, Vipin Kumar. 402-409 [doi]
• SVM Feature Selection for Classification of SPECT Images of Alzheimer s Disease Using Spatial InformationJonathan Stoeckel, Glenn Fung. 410-417 [doi]
• Neighborhood Formation and Anomaly Detection in Bipartite GraphsJimeng Sun, Huiming Qu, Deepayan Chakrabarti, Christos Faloutsos. 418-425 [doi]
• A Border-Based Approach for Hiding Sensitive Frequent ItemsetsXingzhi Sun, Philip S. Yu. 426-433 [doi]
• X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is UnknownZoltán Szamonek, Csaba Szepesvári. 434-441 [doi]
• A Random Walk through Human AssociationsRaz Tamir. 442-449 [doi]
• Supervised Tensor LearningDacheng Tao, Xuelong Li, Weiming Hu, Stephen J. Maybank, Xindong Wu. 450-457 [doi]
• A Bernoulli Relational Model for Nonlinear EmbeddingGang Wang, Hui Zhang, Zhihua Zhang, Frederick H. Lochovsky. 458-465 [doi]
• Template-Based Privacy Preservation in Classification ProblemsKe Wang, Benjamin C. M. Fung, Philip S. Yu. 466-473 [doi]
• On Reducing Classifier Granularity in Mining Concept-Drifting Data StreamsPeng Wang, Haixun Wang, Xiaochen Wu, Wei Wang, Baile Shi. 474-481 [doi]
• Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and ApproximationYongge Wang, Xintao Wu. 482-489 [doi]
• Atomic Wedgie: Efficient Query Filtering for Streaming Times SeriesLi Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto. 490-497 [doi]
• Discriminatively Trained Markov Model for Sequence ClassificationOksana Yakhnenko, Adrian Silvescu, Vasant Honavar. 498-505 [doi]
• Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series ClusteringJie Yin, Qiang Yang. 506-513 [doi]
• Discriminant Analysis: A Unified ApproachPeng Zhang, Norbert Riedel. 514-521 [doi]
• Sharing Classifiers among Ensembles from Related Problem DomainsYi Zhang, W. Nick Street, Samuel Burer. 522-529 [doi]
• A Visual Data Mining Framework for Convenient Identification of Useful KnowledgeKaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xiao. 530-537 [doi]
• Efficient Text Classification by Weighted Proximal SVMDong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zheng Chen, Ying Chen. 538-545 [doi]
• A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation IndexesHidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi. 549-552 [doi]
• Mining Chains of RelationsFoto N. Afrati, Gautam Das, Aristides Gionis, Heikki Mannila, Taneli Mielikäinen, Panayiotis Tsaparas. 553-556 [doi]
• A Preference Model for Structured Supervised Learning TasksFabio Aiolli. 557-560 [doi]
• Blocking Anonymity Threats Raised by Frequent Itemset MiningMaurizio Atzori, Francesco Bonchi, Fosca Giannotti, Dino Pedreschi. 561-564 [doi]
• Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past ExperienceAbraham Bagherjeiran, Christoph F. Eick, Chun-Sheng Chen, Ricardo Vilalta. 565-568 [doi]
• Semi-Supervised Mixture of Kernels via LPBoost MethodsJinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao. 569-572 [doi]
• A Levelwise Search Algorithm for Interesting Subspace ClustersHaiyun Bian, Raj Bhatnagar. 573-576 [doi]
• Segment-Based Injection Attacks against Collaborative Filtering Recommender SystemsRobin D. Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams. 577-580 [doi]
• On Feature Selection through ClusteringRichard Butterworth, Gregory Piatetsky-Shapiro, Dan A. Simovici. 581-584 [doi]
• Sequential Pattern Mining in Multiple StreamsGong Chen, Xindong Wu, Xingquan Zhu. 585-588 [doi]
• Privacy Preserving Data Classification with Rotation PerturbationKeke Chen, Ling Liu. 589-592 [doi]
• A Computational Framework for Taxonomic Research: Diagnosing Body Shape within Fish Species ComplexesYixin Chen, Henry L. Bart Jr., Shuqing Huang, Huimin Chen. 593-596 [doi]
• Obtaining Best Parameter Values for Accurate ClassificationFrans Coenen, Paul H. Leng. 597-600 [doi]
• Process Diagnosis via Electrical-Wafer-Sorting Maps ClassificationFederico Di Palma, Giuseppe De Nicolao, Guido Miraglia, Oliver M. Donzelli. 601-604 [doi]
• An Improved Categorization of Classifier s Sensitivity on Sample Selection BiasWei Fan, Ian Davidson, Bianca Zadrozny, Philip S. Yu. 605-608 [doi]
• Fast Frequent String Mining Using Suffix ArraysJohannes Fischer, Volker Heun, Stefan Kramer. 609-612 [doi]
• Privacy-Preserving Frequent Pattern Mining across Private DatabasesAda Wai-Chee Fu, Raymond Chi-Wing Wong, Ke Wang. 613-616 [doi]
• CoLe: A Cooperative Data Mining Approach and Its Application to Early Diabetes DetectionJie Gao, Jörg Denzinger, Robert C. James. 617-620 [doi]
• Feature Selection for Building Cost-Effective Data Stream ClassifiersLike Gao, Xiaoyang Sean Wang. 621-624 [doi]
• A Scalable Collaborative Filtering Framework Based on Co-ClusteringThomas George, Srujana Merugu. 625-628 [doi]
• Text Classification with Evolving Label-SetsShantanu Godbole, Ganesh Ramakrishnan, Sunita Sarawagi. 629-632 [doi]
• CloseMiner: Discovering Frequent Closed Itemsets Using Frequent Closed TidsetsNingthoujam Gourakishwar Singh, Sanasam Ranbir Singh, Anjana K. Mahanta. 633-636 [doi]
• A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering CriteriaMaria Halkidi, Dimitrios Gunopulos, Nitin Kumar, Michalis Vazirgiannis, Carlotta Domeniconi. 637-640 [doi]
• Focused Community DiscoveryKirsten Hildrum, Philip S. Yu. 641-644 [doi]
• Suppressing Data Sets to Prevent Discovery of Association RulesAyça Azgin Hintoglu, Ali Inan, Yücel Saygin, Mehmet Keskinöz. 645-648 [doi]
• Triple Jump Acceleration for the EM AlgorithmHan-Shen Huang, Bou-Ho Yang, Chun-Nan Hsu. 649-652 [doi]
• Partial Ensemble Classifiers Selection for Better RankingJin Huang, Charles X. Ling. 653-656 [doi]
• Pairwise Symmetry Decomposition Method for Generalized Covariance AnalysisTsuyoshi Idé. 657-660 [doi]
• FS:::3:::: A Random Walk Based Free-Form Spatial Scan Statistic for Anomalous Window DetectionVandana Pursnani Janeja, Vijayalakshmi Atluri. 661-664 [doi]
• Mining Ontological Knowledge from Domain-Specific Text DocumentsXing Jiang, Ah-Hwee Tan. 665-668 [doi]
• Mining Patterns That Respond to ActionsYuelong Jiang, Ke Wang, Alexander Tuzhilin, Ada Wai-Chee Fu. 669-672 [doi]
• Supervised Ordering - An Empirical SurveyToshihiro Kamishima, Hideto Kazawa, Shotaro Akaho. 673-676 [doi]
• Categorization and Keyword Identification of Unlabeled DocumentsNing Kang, Carlotta Domeniconi, Daniel Barbará. 677-680 [doi]
• Gradual Model Generator for Single-Pass ClusteringIsmo Kärkkäinen, Pasi Fränti. 681-684 [doi]
• Making Logistic Regression a Core Data Mining Tool with TR-IRLSPaul Komarek, Andrew W. Moore. 685-688 [doi]
• Hierarchical Density-Based Clustering of Uncertain DataHans-Peter Kriegel, Martin Pfeifle. 689-692 [doi]
• Semi-Supervised Clustering with Metric Learning Using Relative ComparisonsNimit Kumar, Krishna Kummamuru, Deepa Paranjpe. 693-696 [doi]
• On Learning Asymmetric Dissimilarity MeasuresKrishna Kummamuru, Raghu Krishnapuram, Rakesh Agrawal. 697-700 [doi]
• Partial Elastic Matching of Time SeriesLongin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakämper, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh. 701-704 [doi]
• CLUGO: A Clustering Algorithm for Automated Functional Annotations Based on Gene OntologyIn-Yee Lee, Jan-Ming Ho, Ming-Syan Chen. 705-708 [doi]
• An Optimal Linear Time Algorithm for Quasi-Monotonic SegmentationDaniel Lemire, Martin Brooks, Yuhong Yan. 709-712 [doi]
• Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian DatabasesLoïck Lhote, François Rioult, Arnaud Soulet. 713-716 [doi]
• Predicting Software Escalations with Maximum ROICharles X. Ling, Shengli Sheng, Tilmann F. W. Bruckhaus, Nazim H. Madhavji. 717-720 [doi]
• Mining Approximate Frequent Itemsets from Noisy DataJinze Liu, Susan Paulsen, Wei Wang 0010, Andrew B. Nobel, Jan Prins. 721-724 [doi]
• Text Representation: From Vector to TensorNing Liu, Benyu Zhang, Jun Yan, Zheng Chen, Wenyin Liu, Fengshan Bai, Leefeng Chien. 725-728 [doi]
• Parallel Algorithms for Distance-Based and Density-Based OutliersElio Lozano, Edgar Acuña. 729-732 [doi]
• Bit Reduction Support Vector MachineTong Luo, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen. 733-736 [doi]
• Spatial Clustering of Chimpanzee Locations for Neighborhood IdentificationSandeep Mane, Carson Murray, Shashi Shekhar, Jaideep Srivastava, Anne Pusey. 737-740 [doi]
• A Graph-Ranking Algorithm for Geo-Referencing DocumentsBruno Martins, Mário J. Silva. 741-744 [doi]
• An Expected Utility Approach to Active Feature-Value AcquisitionPrem Melville, Foster J. Provost, Raymond J. Mooney. 745-748 [doi]
• Automatically Mining Result Records from Search Engine Response PagesDheerendranath Mundluru, Jayasimha Reddy Katukuri, Saygin Celebi. 749-752 [doi]
• Efficiently Mining Frequent Closed Partial OrdersJian Pei, Jian Liu, Haixun Wang, Ke Wang, Philip S. Yu, Jianyong Wang. 753-756 [doi]
• CLUMP: A Scalable and Robust Framework for Structure DiscoveryKunal Punera, Joydeep Ghosh. 757-760 [doi]
• On the Tractability of Rule Discovery from Distributed DataMartin Scholz. 761-764 [doi]
• Face Recognition Using Landmark-Based Bidimensional RegressionJiazheng Shi, Ashok Samal, David Marx. 765-768 [doi]
• Instability of Classifiers on Categorical DataArno Siebes, Muhammad Subianto, A. J. Feelders. 769-772 [doi]
• Pruning Social Networks Using Structural Properties and Descriptive AttributesLisa Singh, Lise Getoor, Louis Licamele. 773-776 [doi]
• Optimizing Constraint-Based Mining by Automatically Relaxing ConstraintsArnaud Soulet, Bruno Crémilleux. 777-780 [doi]
• Bias Analysis in Text Classification for Highly Skewed DataLei Tang, Huan Liu. 781-784 [doi]
• Efficient Mining of High Branching Factor Attribute TreesAlexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda. 785-788 [doi]
• Anomaly Intrusion Detection Using Multi-Objective Genetic Fuzzy System and Agent-Based Evolutionary Computation FrameworkChi-Ho Tsang, Sam Kwong, Hanli Wang. 789-792 [doi]
• Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace ClusteringTakashi Washio, Yuki Mitsunaga, Hiroshi Motoda. 793-796 [doi]
• Hot Item Mining and Summarization from Multiple Auction Web SitesTak-Lam Wong, Wai Lam. 797-800 [doi]
• Merging Interface Schemas on the Deep Web via Clustering AggregationWensheng Wu, AnHai Doan, Clement T. Yu. 801-804 [doi]
• On the Stationarity of Multivariate Time Series for Correlation-Based Data AnalysisKiyoung Yang, Cyrus Shahabi. 805-808 [doi]
• Speculative Markov Blanket Discovery for Optimal Feature SelectionSandeep Yaramakala, Dimitris Margaritis. 809-812 [doi]
• A Join-Less Approach for Co-Location Pattern Mining: A Summary of ResultsJin Soung Yoo, Shashi Shekhar, Mete Celik. 813-816 [doi]
• Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation TreesKun Zhang, Zujia Xu, Jing Peng, Bill P. Buckles. 817-820 [doi]
• Visualizing Global Manifold Based on Distributed Local Data AbstractionsXiaofeng Zhang, William K. Cheung. 821-824 [doi]
• Bagging with Adaptive CostsYi Zhang, W. Nick Street. 825-828 [doi]
• Example-Based Robust Outlier Detection in High Dimensional DatasetsCui Zhu, Hiroyuki Kitagawa, Christos Faloutsos. 829-832 [doi]
• CTC - Correlating Tree Patterns for ClassificationAlbrecht Zimmermann, Björn Bringmann. 833-836 [doi]