CSDL - Proceedings I

Welcome to ICDM 2005 (PDF)

pp. xvi-xvii

Conference Organization (PDF)

pp. xviii-xix

Steering Committee (PDF)

pp. xx

Program Committee (PDF)

pp. xxi-xxiv

Non-PC Reviewers (PDF)

pp. xxv-xxvi

Invited Talks (PDF)

pp. 837-838

Tutorials (PDF)

pp. 839

Workshops (PDF)

pp. 840

Panel Session (PDF)

pp. 841

Regular Papers

Handling Generalized Cost Functions in the Partitioning Optimization Problem through Sequential Binary Programming (Abstract)

Alan S. Abrahams, University of Pennsylvania

Adrian Becker, University of Pennsylvania

Daniel Fleder, University of Pennsylvania

Ian C. MacMillan, University of Pennsylvania

pp. 3-9

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Online Hierarchical Clustering in a Data Warehouse Environment (Abstract)

Elke Achtert, University of Munich

Christian Böhm, University of Munich

Hans-Peter Kriegel, University of Munich

Peer Kröger, University of Munich

pp. 10-17

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eMailSift: Email Classification Based on Structure and Content (Abstract)

Manu Aery, University of Texas at Arlington

Sharma Chakravarthy, University of Texas at Arlington

pp. 18-25

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An Empirical Bayes Approach to Detect Anomalies in Dynamic Multidimensional Arrays (Abstract)

Deepak Agarwal, AT&T Labs-Research

pp. 26-33

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Classifier Fusion Using Shared Sampling Distribution for Boosting (Abstract)

Costin Barbu, Tulane University

Raja Iqbal, Tulane University

Jing Peng, Tulane University

pp. 34-41

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Improving Automatic Query Classification via Semi-Supervised Learning (Abstract)

Steven M. Beitzel, Information Retrieval Laboratory

Eric C. Jensen, Information Retrieval Laboratory

Ophir Frieder, Information Retrieval Laboratory

David D. Lewis, America Online, Inc.

Abdur Chowdhury, America Online, Inc.

Aleksander Kołcz, America Online, Inc.

pp. 42-49

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ViVo: Visual Vocabulary Construction for Mining Biomedical Images (Abstract)

Arnab Bhattacharya, University of California at Santa Barbara

Vebjorn Ljosa, University of California at Santa Barbara

Jia-Yu Pan, Carnegie Mellon University

Mark R. Verardo, University of California at Santa Barbara

Hyungjeong Yang, Chonnam National University

Christos Faloutsos, Carnegie Mellon University

Ambuj K. Singh, University of California at Santa Barbara

pp. 50-57

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Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping (Abstract)

Mikhail Bilenko, University of Texas at Austin

Sugato Basu, University of Texas at Austin

Mehran Sahami, Google Inc.

pp. 58-65

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Using Information-Theoretic Measures to Assess Association Rule Interestingness (Abstract)

Julien Blanchard, Polytechnic School of Nantes University

Fabrice Guillet, Polytechnic School of Nantes University

Régis Gras, Polytechnic School of Nantes University

Henri Briand, Polytechnic School of Nantes University

pp. 66-73

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Shortest-Path Kernels on Graphs (Abstract)

Karsten M. Borgwardt, Ludwig-Maximilians-University Munich

Hans-Peter Kriegel, Ludwig-Maximilians-University Munich

pp. 74-81

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Mining Frequent Spatio-Temporal Sequential Patterns (Abstract)

Huiping Cao, University of Hong Kong

Nikos Mamoulis, University of Hong Kong

David W. Cheung, University of Hong Kong

pp. 82-89

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Modeling Multiple Time Series for Anomaly Detection (Abstract)

Philip K. Chan, Florida Institute of Technology

Matthew V. Mahoney, Florida Institute of Technology

pp. 90-97

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Summarization — Compressing Data into an Informative Representation (Abstract)

Varun Chandola, University of Minnesota

Vipin Kumar, University of Minnesota

pp. 98-105

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Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values (Abstract)

Hung-Leng Chen, National Taiwan University

Kun-Ta Chuang, National Taiwan University

Ming-Syan Chen, National Taiwan University

pp. 106-113

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Making Subsequence Time Series Clustering Meaningful (Abstract)

Jason R. Chen, Australian National University

pp. 114-121

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Kernel-Density-Based Clustering of Time Series Subsequences Using a Continuous Random-Walk Noise Model (Abstract)

Anne Denton, North Dakota State University

pp. 122-129

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Usage-Based PageRank for Web Personalization (Abstract)

Magdalini Eirinaki, Athens University of Economics and Business

Michalis Vazirgiannis, Athens University of Economics and Business

pp. 130-137

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WARP: Time Warping for Periodicity Detection (Abstract)

Mohamed G. Elfeky, Google Inc.

Walid G. Aref, Purdue University

Ahmed K. Elmagarmid, Purdue University

pp. 138-145

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Bifold Constraint-Based Mining by Simultaneous Monotone and Anti-Monotone Checking (Abstract)

Mohammad El-Hajj, University of Alberta Edmonton

Osmar R. Zaïane, University of Alberta Edmonton

Paul Nalos, University of Alberta Edmonton

pp. 146-153

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Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches (Abstract)

Wei Fan, IBM T.J.Watson Research

Ed Greengrass, US Department of Defense

Joe McCloskey, US Department of Defense

Philip S. Yu, IBM T.J.Watson Research

Kevin Drummey, US Department of Defense

pp. 154-161

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A Thorough Experimental Study of Datasets for Frequent Itemsets (Abstract)

Frédéric Flouvat, Laboratoire LIMOS, UMR CNRS and Université Clermont-Ferrand II

Fabien De Marchi, Laboratoire LIRIS, UMR CNRS and Université Lyon I

Jean-Marc Petit, Laboratoire LIRIS, UMR CNRS and INSA Lyon

pp. 162-169

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AMIOT: Induced Ordered Tree Mining in Tree-Structured Databases (Abstract)

Shohei Hido, Kyoto University

Hiroyuki Kawano, Nanzan University

pp. 170-177

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Hierarchy-Regularized Latent Semantic Indexing (Abstract)

Yi Huang, University of Munich

Kai Yu, Siemens Corporate Technology

Matthias Schubert, University of Munich

Shipeng Yu, University of Munich

Volker Tresp, Siemens Corporate Technology

Hans-Peter Kriegel, University of Munich

pp. 178-185

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Extracting Frequent Subsequences from a Single Long Data Sequence: A Novel Anti-Monotonic Measure and a Simple On-Line Algorithm (Abstract)

Koji Iwanuma, University of Yamanashi

Ryuichi Ishihara, University of Yamanashi

Yo Takano, University of Yamanashi

Hidetomo Nabeshima, University of Yamanashi

pp. 186-193

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Mining Minimal Distinguishing Subsequence Patterns with Gap Constraints (Abstract)

Xiaonan Ji, University of Melbourne

James Bailey, University of Melbourne

Guozhu Dong, Wright State University

pp. 194-201

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Learning Instance Greedily Cloning Naive Bayes for Ranking (Abstract)

Liangxiao Jiang, China University of Geosciences

Harry Zhang, University of New Brunswick

pp. 202-209

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An Algorithm for In-Core Frequent Itemset Mining on Streaming Data (Abstract)

Ruoming Jin, Kent State University

Gagan Agrawal, Ohio State University

pp. 210-217

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Stability of Feature Selection Algorithms (Abstract)

Alexandros Kalousis, University of Geneva

Julien Prados, University of Geneva

Melanie Hilario, University of Geneva

pp. 218-225

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HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence (Abstract)

Eamonn Keogh, University of California at Riverside

Jessica Lin, University of California at Riverside

Ada Fu, Chinese University of Hong Kong

pp. 226-233

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Orthogonal Neighborhood Preserving Projections (Abstract)

E. Kokiopoulou, University of Minnesota

Y. Saad, University of Minnesota

pp. 234-241

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Higher-Order Web Link Analysis Using Multilinear Algebra (Abstract)

Tamara G. Kolda, Sandia National Laboratories

Brett W. Bader, Sandia National Laboratories

Joseph P. Kenny, Sandia National Laboratories

pp. 242-249

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A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data (Abstract)

Hans-Peter Kriegel, University of Munich

Peer Kröger, University of Munich

Matthias Renz, University of Munich

Sebastian Wurst, University of Munich

pp. 250-257

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Effective and Efficient Distributed Model-Based Clustering (Abstract)

Hans-Peter Kriegel, University of Munich

Peer Kröger, University of Munich

Alexey Pryakhin, University of Munich

Matthias Schubert, University of Munich

pp. 258-265

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Finding Maximal Frequent Itemsets over Online Data Streams Adaptively (Abstract)

Daesu Lee, Yonsei University

Wonsuk Lee, Yonsei University

pp. 266-273

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CanTree: A Tree Structure for Efficient Incremental Mining of Frequent Patterns (Abstract)

Carson Kai-Sang Leung, University of Manitoba

Quamrul I. Khan, University of Manitoba

Tariqul Hoque, University of Manitoba

pp. 274-281

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Combining Multiple Clusterings by Soft Correspondence (Abstract)

Bo Long, State University of New York at Binghamton

Zhongfei (Mark) Zhang, State University of New York at Binghamton

Philip S. Yu, IBM T. J. Watson Research Center

pp. 282-289

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A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment (Abstract)

A. M. Manning, University of Manchester

D. J. Haglin, Minnesota State University

pp. 290-297

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Alternate Representation of Distance Matrices for Characterization of Protein Structure (Abstract)

Keith Marsolo, Ohio State University

Srinivasan Parthasarathy, Ohio State University

pp. 298-305

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Training Support Vector Machines Using Gilbert?s Algorithm (Abstract)

Shawn Martin, Sandia National Laboratories

pp. 306-313

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A Heterogeneous Field Matching Method for Record Linkage (Abstract)

Steven N. Minton, Fetch Technologies

Claude Nanjo, Fetch Technologies

Craig A. Knoblock, University of Southern California

Martin Michalowski, University of Southern California

Matthew Michelson, University of Southern California

pp. 314-321

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Leveraging Relational Autocorrelation with Latent Group Models (Abstract)

Jennifer Neville, University of Massachusetts at Amherst

David Jensen, University of Massachusetts at Amherst

pp. 322-329

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Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning (Abstract)

Thomas Osugi, University of Nebraska

Deng Kun, University of Nebraska

Stephen Scott, University of Nebraska

pp. 330-337

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Finding Representative Set from Massive Data (Abstract)

Feng Pan, University of North Carolina at Chapel Hill

Wei Wang, University of North Carolina at Chapel Hill

Anthony K. H. Tung, National University of Singapore

Jiong Yang, Case Western Reserve University

pp. 338-345

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Parameter-Free Spatial Data Mining Using MDL (Abstract)

Spiros Papadimitriou, Carnegie Mellon University

Aristides Gionis, University of Helsinki

Panayiotis Tsaparas, University of Helsinki

Risto A. Väisänen, University of Helsinki

Heikki Mannila, University of Helsinki

Christos Faloutsos, Carnegie Mellon University

pp. 346-353

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Discovering Frequent Arrangements of Temporal Intervals (Abstract)

Panagiotis Papapetrou, Boston University

George Kollios, Boston University

Stan Sclaroff, Boston University

Dimitrios Gunopulos, University of California at Riverside

pp. 354-361

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Mining Patterns of Change in Remote Sensing Image Databases (Abstract)

Marcelino Pereira S. Silva, Rio Grande do Norte State University and National Institute for Space Research

Gilberto Câmara, National Institute for Space Research

Ricardo Cartaxo M. Souza, National Institute for Space Research

Dalton M. Valeriano, National Institute for Space Research

Maria Isabel S. Escada, National Institute for Space Research

pp. 362-369

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Ranking-Based Evaluation of Regression Models (Abstract)

Saharon Rosset, IBM T. J. Watson Research Center

Claudia Perlich, IBM T. J. Watson Research Center

Bianca Zadrozny, IBM T. J. Watson Research Center

pp. 370-377

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Compound Classification Models for Recommender Systems (Abstract)

Lars Schmidt-Thieme, University of Freiburg

pp. 378-385

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Multi-Stage Classification (Abstract)

Ted E. Senator, DARPA/IPTO

pp. 386-393

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Learning Functional Dependency Networks Based on Genetic Programming (Abstract)

Wing-Ho Shum, Chinese University of Hong Kong

Kwong-Sak Leung, Chinese University of Hong Kong

Man-Leung Wong, Lingnan University

pp. 394-401

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Generalizing the Notion of Confidence (Abstract)

Michael Steinbach, University of Minnesota

Vipin Kumar, University of Minnesota

pp. 402-409

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SVM Feature Selection for Classification of SPECT Images of Alzheimer?s Disease Using Spatial Information (Abstract)

Jonathan Stoeckel, Siemens Medical Solutions USA

Glenn Fung, Siemens Medical Solutions USA

pp. 410-417

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Neighborhood Formation and Anomaly Detection in Bipartite Graphs (Abstract)

Jimeng Sun, Carnegie Mellon University

Huiming Qu, University of Pittsburgh

Deepayan Chakrabarti, Yahoo! Research

Christos Faloutsos, Carnegie Mellon University

pp. 418-425

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A Border-Based Approach for Hiding Sensitive Frequent Itemsets (Abstract)

Xingzhi Sun, University of Queensland

Philip S. Yu, IBM T. J. Watson Research Center

pp. 426-433

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X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is Unknown (Abstract)

Zoltán Szamonek, Hungarian Academy of Sciences and Eötvös University Budapest

Csaba Szepesvári, Hungarian Academy of Sciences

pp. 434-441

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A Random Walk through Human Associations (Abstract)

Raz Tamir, Hebrew University of Jerusalem

pp. 442-449

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Supervised Tensor Learning (Abstract)

Dacheng Tao, University of London

Xuelong Li, University of London

Weiming Hu, Chinese Academy of Science

Stephen Maybank, University of London

Xindong Wu, University of Vermont

pp. 450-457

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A Bernoulli Relational Model for Nonlinear Embedding (Abstract)

Gang Wang, Hong Kong University of Science and Technology

Hui Zhang, Xi?an Jiaotong University

Zhihua Zhang, Hong Kong University of Science and Technology

Frederick H. Lochovsky, Hong Kong University of Science and Technology

pp. 458-465

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Template-Based Privacy Preservation in Classification Problems (Abstract)

Ke Wang, Simon Fraser University

Benjamin C. M. Fung, Simon Fraser University

Philip S. Yu, IBM T. J. Watson Research Center

pp. 466-473

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On Reducing Classifier Granularity in Mining Concept-Drifting Data Streams (Abstract)

Peng Wang, Fudan University

Haixun Wang, IBM T. J. Watson Research Center

Xiaochen Wu, Fudan University

Wei Wang, Fudan University

Baile Shi, Fudan University

pp. 474-481

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Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation (Abstract)

Yongge Wang, University of North Carolina at Charlotte

Xintao Wu, University of North Carolina at Charlotte

pp. 482-489

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Atomic Wedgie: Efficient Query Filtering for Streaming Times Series (Abstract)

Li Wei, University of California at Riverside

Eamonn Keogh, University of California at Riverside

Helga Van Herle, University of California at Los Angeles

Agenor Mafra-Neto, ISCA Technologies

pp. 490-497

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Discriminatively Trained Markov Model for Sequence Classification (Abstract)

Oksana Yakhnenko, Iowa State University

Adrian Silvescu, Iowa State University

Vasant Honavar, Iowa State University

pp. 498-505

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Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering (Abstract)

Jie Yin, Hong Kong University of Science and Technology

Qiang Yang, Hong Kong University of Science and Technology

pp. 506-513

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Discriminant Analysis: A Unified Approach (Abstract)

Peng Zhang, Tulane University

Norbert Riedel, Tulane University

pp. 514-521

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Sharing Classifiers among Ensembles from Related Problem Domains (Abstract)

Yi Zhang, University of Iowa

W. Nick Street, University of Iowa

Samuel Burer, University of Iowa

pp. 522-529

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A Visual Data Mining Framework for Convenient Identification of Useful Knowledge (Abstract)

Kaidi Zhao, University of Illinois at Chicago

Bing Liu, University of Illinois at Chicago

Thomas M. Tirpak, Motorola Labs

Weimin Xiao, Motorola Labs

pp. 530-537

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Efficient Text Classification by Weighted Proximal SVM (Abstract)

Dong Zhuang, Beijing Institute of Technology

Benyu Zhang, Microsoft Research Asia

Qiang Yang, Hong Kong University of Science and Technology

Jun Yan, Peking University

Zheng Chen, Microsoft Research Asia

Ying Chen, Beijing Institute of Technology

pp. 538-545

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Short Papers

A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes (Abstract)

Hidenao Abe, Shimane University

Shusaku Tsumoto, Shimane University

Miho Ohsaki, Doshisha University

Takahira Yamaguchi, Keio University

pp. 549-552

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Mining Chains of Relations (Abstract)

Foto Afrati, National Technical University of Athens

Gautam Das, National Technical University of Athens

Aristides Gionis, University of Helsinki

Heikki Mannila, University of Helsinki

Taneli Mielikäinen, University of Helsinki

Panayiotis Tsaparas, University of Helsinki

pp. 553-556

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A Preference Model for Structured Supervised Learning Tasks (Abstract)

Fabio Aiolli, Università di Padova

pp. 557-560

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Blocking Anonymity Threats Raised by Frequent Itemset Mining (Abstract)

Maurizio Atzori, ISTI - CNR and University of Pisa

Francesco Bonchi, ISTI - CNR

Fosca Giannotti, ISTI - CNR

Dino Pedreschi, University of Pisa

pp. 561-564

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Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience (Abstract)

Abraham Bagherjeiran, University of Houston

Christoph F. Eick, University of Houston

Chun-Sheng Chen, University of Houston

Ricardo Vilalta, University of Houston

pp. 565-568

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Semi-Supervised Mixture of Kernels via LPBoost Methods (Abstract)

Jinbo Bi, Siemens Medical Solutions

Glenn Fung, Siemens Medical Solutions

Murat Dundar, Siemens Medical Solutions

Bharat Rao, Siemens Medical Solutions

pp. 569-572

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A Levelwise Search Algorithm for Interesting Subspace Clusters (Abstract)

Haiyun Bian, University of Cincinnati

Raj Bhatnagar, University of Cincinnati

pp. 573-576

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Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems (Abstract)

Robin Burke, DePaul University

Bamshad Mobasher, DePaul University

Runa Bhaumik, DePaul University

Chad Williams, DePaul University

pp. 577-580

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On Feature Selection through Clustering (Abstract)

Richard Butterworth, University of Massachusetts at Boston

Gregory Piatetsky-Shapiro, KDnuggets

Dan A. Simovici, University of Massachusetts at Boston

pp. 581-584

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Sequential Pattern Mining in Multiple Streams (Abstract)

Gong Chen, University of Vermont

Xindong Wu, University of Vermont

Xingquan Zhu, University of Vermont

pp. 585-588

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Privacy Preserving Data Classification with Rotation Perturbation (Abstract)

Keke Chen, Georgia Institute of Technology

Ling Liu, Georgia Institute of Technology

pp. 589-592

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A Computational Framework for Taxonomic Research: Diagnosing Body Shape within Fish Species Complexes (Abstract)

Yixin Chen, University of New Orleans

Henry L. Bart, Jr., Tulane University

Shuqing Huang, Tulane University

Huimin Chen, Tulane University

pp. 593-596

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Obtaining Best Parameter Values for Accurate Classification (Abstract)

Frans Coenen, University of Liverpool

Paul Leng, University of Liverpool

pp. 597-600

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Process Diagnosis via Electrical-Wafer-Sorting Maps Classification (Abstract)

Federico Di Palma, University of Pavia

Giuseppe De Nicolao, University of Pavia

Guido Miraglia, ST Microelectronics

Oliver M. Donzelli, ST Microelectronics

pp. 601-604

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An Improved Categorization of Classifier?s Sensitivity on Sample Selection Bias (Abstract)

Wei Fan, IBM T. J. Watson Research

Ian Davidson, State University of New York at Albany

Bianca Zadrozny, IBM T. J. Watson Research

Philip S. Yu, IBM T. J. Watson Research

pp. 605-608

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Fast Frequent String Mining Using Suffix Arrays (Abstract)

Johannes Fischer, Universität München

Volker Heun, Universität München

Stefan Kramer, TU München

pp. 609-612

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Privacy-Preserving Frequent Pattern Mining across Private Databases (Abstract)

Ada Wai-Chee Fu, Chinese University of Hong Kong

Raymond Chi-Wing Wong, Chinese University of Hong Kong

Ke Wang, Simon Fraser University

pp. 613-616

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CoLe: A Cooperative Data Mining Approach and Its Application to Early Diabetes Detection (Abstract)

Jie Gao, University of Calgary

Jörg Denzinger, University of Calgary

Robert C. James, Aechidna Health Informatics

pp. 617-620

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Feature Selection for Building Cost-Effective Data Stream Classifiers (Abstract)

Like Gao, University of Vermont

X. Sean Wang, University of Vermont

pp. 621-624

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A Scalable Collaborative Filtering Framework Based on Co-Clustering (Abstract)

Thomas George, Texas A & M University

Srujana Merugu, University of Texas at Austin

pp. 625-628

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Text Classification with Evolving Label-Sets (Abstract)

Shantanu Godbole, Indian Institute of Technology - Bombay

Ganesh Ramakrishnan, IBM India Research Lab

Sunita Sarawagi, Indian Institute of Technology - Bombay

pp. 629-632

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CloseMiner: Discovering Frequent Closed Itemsets Using Frequent Closed Tidsets (Abstract)

N. Gourakishwar Singh, Manipur University

S. Ranbir Singh, Manipur University

Anjana K. Mahanta, Gauhati University

pp. 633-636

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A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria (Abstract)

M. Halkidi, University of California at Riverside and Athens University of Economics and Business

D. Gunopulos, University of California at Riverside

N. Kumar, University of California at Riverside

M. Vazirgiannis, Athens University of Economics and Business

C. Domeniconi, George Mason University

pp. 637-640

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Focused Community Discovery (Abstract)

Kirsten Hildrum, IBM T.J. Watson Research Center

Philip S. Yu, IBM T.J. Watson Research Center

pp. 641-644

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Suppressing Data Sets to Prevent Discovery of Association Rules (Abstract)

Ayça Azgin Hintoğlu, Sabanci University

Ali Inan, Sabanci University

Yücel Saygin, Sabanci University

Mehmet Keskinöz, Sabanci University

pp. 645-648

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Triple Jump Acceleration for the EM Algorithm (Abstract)

Han-Shen Huang, Academia Sinica

Bou-Ho Yang, Academia Sinica and Chang Gung University

Chun-Nan Hsu, Academia Sinica

pp. 649-652

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Partial Ensemble Classifiers Selection for Better Ranking (Abstract)

Jin Huang, University of Western Ontario

Charles X. Ling, University of Western Ontario

pp. 653-656

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Pairwise Symmetry Decomposition Method for Generalized Covariance Analysis (Abstract)

Tsuyoshi Idé, IBM Research, Tokyo Research Laboratory

pp. 657-660

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FS³: A Random Walk Based Free-Form Spatial Scan Statistic for Anomalous Window Detection (Abstract)

Vandana P. Janeja, Rutgers University

Vijayalakshmi Atluri, Rutgers University

pp. 661-664

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Mining Ontological Knowledge from Domain-Specific Text Documents (Abstract)

Xing Jiang, Nanyang Technological University

Ah-Hwee Tan, Nanyang Technological University

pp. 665-668

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Mining Patterns That Respond to Actions (Abstract)

Yuelong Jiang, Simon Fraser University

Ke Wang, Simon Fraser University

Alexander Tuzhilin, New York University

Ada Wai-Chee Fu, Chinese University of Hong Kong

pp. 669-672

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Supervised Ordering — An Empirical Survey (Abstract)

Toshihiro Kamishima, National Institute of Advanced Industrial Science and Technology

Hideto Kazawa, Nippon Telegraph and Telephone Corporation

Shotaro Akaho, National Institute of Advanced Industrial Science and Technology

pp. 673-676

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Categorization and Keyword Identification of Unlabeled Documents (Abstract)

Ning Kang, George Mason University

Carlotta Domeniconi, George Mason University

Daniel Barbará, George Mason University

pp. 677-680

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Gradual Model Generator for Single-Pass Clustering (Abstract)

Ismo Kärkkäinen, University of Joensuu

Pasi Fränti, University of Joensuu

pp. 681-684

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Making Logistic Regression a Core Data Mining Tool with TR-IRLS (Abstract)

Paul Komarek, Carnegie Mellon University

Andrew W. Moore, Carnegie Mellon University

pp. 685-688

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Hierarchical Density-Based Clustering of Uncertain Data (Abstract)

Hans-Peter Kriegel, University of Munich

Martin Pfeifle, University of Munich

pp. 689-692

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Semi-Supervised Clustering with Metric Learning Using Relative Comparisons (Abstract)

Nimit Kumar, IBM India Research Lab

Krishna Kummamuru, IBM India Research Lab

Deepa Paranjpe, IBM India Research Lab

pp. 693-696

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On Learning Asymmetric Dissimilarity Measures (Abstract)

Krishna Kummamuru, IBM India Research Lab

Raghu Krishnapuram, IBM India Research Lab

Rakesh Agrawal, IBM Almaden Research Center

pp. 697-700

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Partial Elastic Matching of Time Series (Abstract)

Longin Jan Latecki, Temple University

Vasileios Megalooikonomou, Temple University

Qiang Wang, Temple University

Rolf Lakaemper, Temple University

C. A. Ratanamahatana, University of California at Riverside

E. Keogh, University of California at Riverside

pp. 701-704

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CLUGO: A Clustering Algorithm for Automated Functional Annotations Based on Gene Ontology (Abstract)

In-Yee Lee, National Taiwan University and Academia Sinica

Jan-Ming Ho, Academia Sinica

Ming-Syan Chen, National Taiwan University

pp. 705-708

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An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation (Abstract)

Daniel Lemire, University of Quebec at Montreal

Martin Brooks, National Research Council of Canada

Yuhong Yan, National Research Council of Canada

pp. 709-712

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Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases (Abstract)

Loïck Lhote, Université de Caen Basse-Normandie

François Rioult, Université de Caen Basse-Normandie

Arnaud Soulet, Université de Caen Basse-Normandie

pp. 713-716

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Predicting Software Escalations with Maximum ROI (Abstract)

Charles X. Ling, University of Western Ontario

Shengli Sheng, University of Western Ontario

Tilmann Bruckhaus, Sun Microsystems, Inc.

Nazim H. Madhavji, University of Western Ontario

pp. 717-720

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Mining Approximate Frequent Itemsets from Noisy Data (Abstract)

Jinze Liu, University of North Carolina at Chapel Hill

Susan Paulsen, University of North Carolina at Chapel Hill

Wei Wang, University of North Carolina at Chapel Hill

Andrew Nobel, University of North Carolina at Chapel Hill

Jan Prins, University of North Carolina at Chapel Hill

pp. 721-724

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Text Representation: From Vector to Tensor (Abstract)

Ning Liu, Tsinghua University

Benyu Zhang, Microsoft Research Asia

Jun Yan, Peking University

Zheng Chen, Microsoft Research Asia

Wenyin Liu, City University of Hong Kong

Fengshan Bai, Tsinghua University

Leefeng Chien, Academia Sinica

pp. 725-728

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Parallel Algorithms for Distance-Based and Density-Based Outliers (Abstract)

Elio Lozano, University of Puerto Rico

Edgar Acuña, University of Puerto Rico

pp. 729-732

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Bit Reduction Support Vector Machine (Abstract)

Tong Luo, University of South Florida

Lawrence O. Hall, University of South Florida

Dmitry B. Goldgof, University of South Florida

Andrew Remsen, University of South Florida

pp. 733-736

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Spatial Clustering of Chimpanzee Locations for Neighborhood Identification (Abstract)

Sandeep Mane, University of Minnesota

Carson Murray, University of Minnesota

Shashi Shekhar, University of Minnesota

Jaideep Srivastava, University of Minnesota

Anne Pusey, University of Minnesota

pp. 737-740

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A Graph-Ranking Algorithm for Geo-Referencing Documents (Abstract)

Bruno Martins, Universidade de Lisboa

Mário J. Silva, Universidade de Lisboa

pp. 741-744

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An Expected Utility Approach to Active Feature-Value Acquisition (Abstract)

Prem Melville, University of Texas at Austin

Maytal Saar-Tsechansky, University of Texas at Austin

Foster Provost, New York University

Raymond Mooney, University of Texas at Austin

pp. 745-748

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Automatically Mining Result Records from Search Engine Response Pages (Abstract)

Dheerendranath Mundluru, University of Louisiana at Lafayette

Jayasimha Reddy Katukuri, University of Louisiana at Lafayette

Saygin Celebi, University of Louisiana at Lafayette

pp. 749-752

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Efficiently Mining Frequent Closed Partial Orders (Abstract)

Jian Pei, Simon Fraser University

Jian Liu, State University of New York at Buffalo

Haixun Wang, IBM T.J. Watson Research Center

Ke Wang, Simon Fraser University

Philip S. Yu, IBM T.J. Watson Research Center

Jianyong Wang, Tsinghua University

pp. 753-756

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CLUMP: A Scalable and Robust Framework for Structure Discovery (Abstract)

Kunal Punera, University of Texas at Austin

Joydeep Ghosh, University of Texas at Austin

pp. 757-760

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On the Tractability of Rule Discovery from Distributed Data (Abstract)

Martin Scholz, University of Dortmund

pp. 761-764

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Face Recognition Using Landmark-Based Bidimensional Regression (Abstract)

Jiazheng Shi, University of Nebraska - Lincoln

Ashok Samal, University of Nebraska - Lincoln

David Marx, University of Nebraska - Lincoln

pp. 765-768

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Instability of Classifiers on Categorical Data (Abstract)

Arno Siebes, Universiteit Utrecht

Muhammad Subianto, Universiteit Utrecht

Ad Feelders, Universiteit Utrecht

pp. 769-772

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Pruning Social Networks Using Structural Properties and Descriptive Attributes (Abstract)

Lisa Singh, Georgetown University

Lise Getoor, University of Maryland at College Park

Louis Licamele, University of Maryland at College Park

pp. 773-776

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Optimizing Constraint-Based Mining by Automatically Relaxing Constraints (Abstract)

Arnaud Soulet, Université de Caen

Bruno Crémilleux, Université de Caen

pp. 777-780

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Bias Analysis in Text Classification for Highly Skewed Data (Abstract)

Lei Tang, Arizona State University

Huan Liu, Arizona State University

pp. 781-784

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Efficient Mining of High Branching Factor Attribute Trees (Abstract)

Alexandre Termier, Osaka University

Marie-Christine Rousset, CNRS, Université Paris-Sud and INRIA

Michèle Sebag, CNRS, Université Paris-Sud and INRIA

Kouzou Ohara, Osaka University

Takashi Washio, Osaka University

Hiroshi Motoda, Osaka University

pp. 785-788

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Anomaly Intrusion Detection Using Multi-Objective Genetic Fuzzy System and Agent-Based Evolutionary Computation Framework (Abstract)

Chi-Ho Tsang, City University of Hong Kong

Sam Kwong, City University of Hong Kong

Hanli Wang, City University of Hong Kong

pp. 789-792

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Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering (Abstract)

Takashi Washio, Osaka University

Yuki Mitsunaga, Osaka University

Hiroshi Motoda, Osaka University

pp. 793-796

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Hot Item Mining and Summarization from Multiple Auction Web Sites (Abstract)

Tak-Lam Wong, Chinese University of Hong Kong

Wai Lam, Chinese University of Hong Kong

pp. 797-800

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Merging Interface Schemas on the Deep Web via Clustering Aggregation (Abstract)

Wensheng Wu, University of Illinois at Urbana-Champaign

AnHai Doan, University of Illinois at Urbana-Champaign

Clement Yu, University of Illinois at Chicago

pp. 801-804

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On the Stationarity of Multivariate Time Series for Correlation-Based Data Analysis (Abstract)

Kiyoung Yang, University of Southern California

Cyrus Shahabi, University of Southern California

pp. 805-808

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Speculative Markov Blanket Discovery for Optimal Feature Selection (Abstract)

Sandeep Yaramakala, Iowa State University

Dimitris Margaritis, Iowa State University

pp. 809-812

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A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results (Abstract)

Jin Soung Yoo, University of Minnesota

Shashi Shekhar, University of Minnesota

Mete Celik, University of Minnesota

pp. 813-816

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Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation Trees (Abstract)

Kun Zhang, Tulane University

Zujia Xu, Dillard University

Jing Peng, Tulane University

Bill Buckles, Tulane University

pp. 817-820

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Visualizing Global Manifold Based on Distributed Local Data Abstractions (Abstract)

Xiaofeng Zhang, Hong Kong Baptist University

William K. Cheung, Hong Kong Baptist University

pp. 821-824

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Bagging with Adaptive Costs (Abstract)

Yi Zhang, University of Iowa

W. Nick Street, University of Iowa

pp. 825-828

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Example-Based Robust Outlier Detection in High Dimensional Datasets (Abstract)

Cui Zhu, University of Tsukuba

Hiroyuki Kitagawa, University of Tsukuba

Christos Faloutsos, Carnegie Mellon University

pp. 829-832

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CTC — Correlating Tree Patterns for Classification (Abstract)

Albrecht Zimmermann, Albert-Ludwigs-University Freiburg

Björn Bringmann, Albert-Ludwigs-University Freiburg

pp. 833-836

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Author Index

Author Index (PDF)

pp. 843-846