4. ICDM 2004: Brighton, UK

Regular Papers

• Mikhail J. Atallah, Robert Gwadera, Wojciech Szpankowski:
  Detection of Significant Sets of Episodes in Event Sequences. 3-10
  
• Christian Baumgartner, Claudia Plant, Karin Kailing, Hans-Peter Kriegel, Peer Kröger:
  Subspace Selection for Clustering High-Dimensional Data. 11-18
  
• Steffen Bickel, Tobias Scheffer:
  Multi-View Clustering. 19-26
  
• Christian Böhm, Karin Kailing, Hans-Peter Kriegel, Peer Kröger:
  Density Connected Clustering with Local Subspace Preferences. 27-34
  
• Francesco Bonchi, Claudio Lucchese:
  On Closed Constrained Frequent Pattern Mining. 35-42
  
• Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfeifle:
  Efficient Density-Based Clustering of Complex Objects. 43-50
  
• Xiaoyong Chai, Lin Deng, Qiang Yang, Charles X. Ling:
  Test-Cost Sensitive Naive Bayes Classification. 51-58
  
• Yun Chi, Haixun Wang, Philip S. Yu, Richard R. Muntz:
  Moment: Maintaining Closed Frequent Itemsets over a Stream Sliding Window. 59-66
  
• Chris Giannella, Kun Liu, Todd Olsen, Hillol Kargupta:
  Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data. 67-74
  
• David Gondek, Thomas Hofmann:
  Non-Redundant Data Clustering. 75-82
  
• Anjan Goswami, Ruoming Jin, Gagan Agrawal:
  Fast and Exact Out-of-Core K-Means Clustering. 83-90
  
• Gösta Grahne, Jianfei Zhu:
  Mining Frequent Itemsets from Secondary Memory. 91-98
  
• Jens Gregor, ZhenQiu Liu:
  A Bayesian Framework for Regularized SVM Parameter Estimation. 99-105
  
• Niina Haiminen, Aristides Gionis:
  Unimodal Segmentation of Sequences. 106-113
  
• Heli Hiisilä, Ella Bingham:
  Dependencies between Transcription Factor Binding Sites: Comparison between ICA, NMF, PLSA and Frequent Sets. 114-121
  
• Zheng Huang, Lei Chen, Jin-yi Cai, Deborah S. Gross, David R. Musicant, Raghu Ramakrishnan, James J. Schauer, Stephen J. Wright:
  Mass Spectrum Labeling: Theory and Practice. 122-129
  
• Dae-Ki Kang, Adrian Silvescu, Jun Zhang, Vasant Honavar:
  Generation of Attribute Value Taxonomies from Data for Data-Driven Construction of Accurate and Compact Classifiers. 130-137
  
• Grigoris J. Karakoulas, Ruslan Salakhutdinov:
  Semi-Supervised Mixture-of-Experts Classification. 138-145
  
• Matjaz Kukar:
  Transduction and Typicalness for Quality Assessment of Individual Classifications in Machine Learning and Data Mining. 146-153
  
• Tsau Young Lin:
  Mining Associations by Linear Inequalities. 154-161
  
• Tao Liu, Zheng Chen, Benyu Zhang, Wei-Ying Ma, Gongyi Wu:
  Improving Text Classification using Local Latent Semantic Indexing. 162-169
  
• Jennifer Neville, David Jensen:
  Dependency Networks for Relational Data. 170-177
  
• Laurence A. F. Park, Kotagiri Ramamohanarao:
  Hybrid Pre-Query Term Expansion using Latent Semantic Analysis. 178-185
  
• Karlton Sequeira, Mohammed Javeed Zaki:
  SCHISM: A New Approach for Interesting Subspace Mining. 186-193
  
• B. Shekar, Rajesh Natarajan:
  A Transaction-Based Neighbourhood-Driven Approach to Quantifying Interestingness of Association Rules. 194-201
  
• Antonino Staiano, Lara De Vinco, Angelo Ciaramella, Giancarlo Raiconi, Roberto Tagliaferri, Roberto Amato, Giuseppe Longo, Ciro Donalek, Gennaro Miele, Diego di Bernardo:
  Probabilistic Principal Surfaces for Yeast Gene Microarray Data Mining. 202-208
  
• Pei Sun, Sanjay Chawla:
  On Local Spatial Outliers. 209-216
  
• Fadi A. Thabtah, Peter I. Cowling, Yonghong Peng:
  MMAC: A New Multi-Class, Multi-Label Associative Classification Approach. 217-224
  
• Alexander P. Topchy, Martin H. C. Law, Anil K. Jain, Ana L. N. Fred:
  Analysis of Consensus Partition in Cluster Ensemble. 225-232
  
• Jaideep Vaidya, Chris Clifton:
  Privacy-Preserving Outlier Detection. 233-240
  
• Jianyong Wang, George Karypis:
  SUMMARY: Efficiently Summarizing Transactions for Clustering. 241-248
  
• Ke Wang, Philip S. Yu, Sourav Chakraborty:
  Bottom-Up Generalization: A Data Mining Solution to Privacy Protection. 249-256
  
• Tak-Lam Wong, Wai Lam:
  A Probabilistic Approach for Adapting Information Extraction Wrappers and Discovering New Attributes. 257-264
  
• Gang Wu, Edward Y. Chang:
  Aligning Boundary in Kernel Space for Learning Imbalanced Dataset. 265-272
  
• Gui-Rong Xue, Dou Shen, Qiang Yang, Hua-Jun Zeng, Zheng Chen, Yong Yu, Wensi Xi, Wei-Ying Ma:
  IRC: An Iterative Reinforcement Categorization Algorithm for Interrelated Web Objects. 273-280
  
• Feng Zhang:
  A Polygonal Line Algorithm based Nonlinear Feature Extraction Method. 281-288
  
• Jun Zhang, Vasant Honavar:
  AVT-NBL: An Algorithm for Learning Compact and Accurate Naïve Bayes Classifiers from Attribute Value Taxonomies and Data. 289-296
  
• Xingquan Zhu, Xindong Wu:
  Cost-Guided Class Noise Handling for Effective Cost-Sensitive Learning. 297-304
  
• Xingquan Zhu, Xindong Wu, Ying Yang:
  Dynamic Classifier Selection for Effective Mining from Noisy Data Streams. 305-312
  

Short Papers

• Hamad Alhammady, Kotagiri Ramamohanarao:
  Using Emerging Patterns and Decision Trees in Rare-Class Classification. 315-318
  
• Alexessander Alves, Rui Camacho, Eugenio Oliveira:
  Discovery of Functional Relationships in Multi-Relational Data using Inductive Logic Programming. 319-322
  
• Andrew Arnt, Shlomo Zilberstein:
  Attribute Measurement Policies for Time and Cost Sensitive Classification. 323-326
  
• Michael Baranski, Jürgen Voss:
  Detecting Patterns of Appliances from Total Load Data Using a Dynamic Programming Approach. 327-330
  
• Stephan Bloehdorn, Andreas Hotho:
  Text Classification by Boosting Weak Learners based on Terms and Concepts. 331-334
  
• Björn Bringmann:
  Matching in Frequent Tree Discovery. 335-338
  
• Emilio Carrizosa, Belen Martin-Barragan, Dolores Romero Morales:
  A Biobjective Model to Select Features with Good Classification Quality and Low Cost. 339-342
  
• Yi Chen, Liang Huai Yang, Yu Guo Wang:
  Incremental Mining of Frequent XML Query Pattern. 343-346
  
• Shalendra Chhabra, William S. Yerazunis, Christian Siefkes:
  Spam Filtering using a Markov Random Field Model with Variable Weighting Schemas. 347-350
  
• Fang Chu, Yizhou Wang, Carlo Zaniolo:
  An Adaptive Learning Approach for Noisy Data Streams. 351-354
  
• Amanda Clare, Hugh E. Williams, Nicholas Lester:
  Scalable Multi-Relational Association Mining. 355-358
  
• Frans Coenen, Paul H. Leng:
  An Evaluation of Approaches to Classification Rule Selection. 359-362
  
• Gao Cong, Kian-Lee Tan, Anthony K. H. Tung, Feng Pan:
  Mining Frequent Closed Patterns in Microarray Data. 363-366
  
• Bi-Ru Dai, Jen-Wei Huang, Mi-Yen Yeh, Ming-Syan Chen:
  Clustering on Demand for Multiple Data Streams. 367-370
  
• Margaret H. Dunham, Yu Meng, Jie Huang:
  Extensible Markov Model. 371-374
  
• Christoph F. Eick, Nidal M. Zeidat, Ricardo Vilalta:
  Using Representative-Based Clustering for Nearest Neighbor Dataset Editing. 375-378
  
• Wei Fan, Yi-an Huang, Philip S. Yu:
  Decision Tree Evolution Using Limited Number of Labeled Data Items from Drifting Data Streams. 379-382
  
• Pierre Geurts, Ibtissam El Khayat, Guy Leduc:
  A Machine Learning Approach to Improve Congestion Control over Wireless Computer Networks. 383-386
  
• Amol Ghoting, Matthew Eric Otey, Srinivasan Parthasarathy:
  LOADED: Link-Based Outlier and Anomaly Detection in Evolving Data Sets. 387-390
  
• David Gleich, Leonid Zhukov:
  SVD based Term Suggestion and Ranking System. 391-394
  
• Paolo Ferragina, Antonio Gulli:
  The Anatomy of a Hierarchical Clustering Engine for Web-page, News and Book Snippets. 395-398
  
• Yiqiu Han, Wai Lam:
  Query-Driven Support Pattern Discovery for Classification Learning. 399-402
  
• Eduardo R. Hruschka, Leandro Nunes de Castro, Ricardo J. G. B. Campello:
  Evolutionary Algorithms for Clustering Gene-Expression Data. 403-406
  
• Chenyong Hu, Benyu Zhang, Shuicheng Yan, Qiang Yang, Jun Yan, Zheng Chen, Wei-Ying Ma:
  Mining Ratio Rules Via Principal Sparse Non-Negative Matrix Factorization. 407-410
  
• Ye Huang, Paul J. McCullagh, Norman D. Black:
  Feature Selection via Supervised Model Construction. 411-414
  
• Akihiro Inokuchi:
  Mining Generalized Substructures from a Set of Labeled Graphs. 415-418
  
• Tianyi Jiang, Alexander Tuzhilin:
  Divide and Prosper: Comparing Models of Customer Behavior From Populations to Individuals. 419-422
  
• Toshihiro Kamishima, Shotaro Akaho:
  Filling-in Missing Objects in Orders. 423-426
  
• Hillol Kargupta, Haimonti Dutta:
  Orthogonal Decision Trees. 427-430
  
• Mehmet Kaya, Reda Alhajj:
  ntegrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining. 431-434
  
• Hyungil Kim, Juntae Kim, Jonathan L. Herlocker:
  Feature-Based Prediction of Unknown Preferences for Nearest-Neighbor Collaborative Filtering. 435-438
  
• Michihiro Kuramochi, George Karypis:
  GREW-A Scalable Frequent Subgraph Discovery Algorithm. 439-442
  
• Chih Lai, Nga T. Nguyen:
  Predicting Density-Based Spatial Clusters Over Time. 443-446
  
• Beng-Seuk Lee, Trevor P. Martin, Nick P. Clarke, Basim A. Majeed, Detlef Nauck:
  Dynamic Daily-Living Patterns and Association Analyses in Tele-Care Systems. 447-450
  
• Tao Li, Sheng Ma:
  Mining Temporal Patterns Without Predefined Time Windows. 451-454
  
• Xiaoli Li, Rohit Joshi, Sreeram Ramachandaran, Tze-Yun Leong:
  Classifying Biomedical Citations without Labeled Training Examples. 455-458
  
• David G. Lindsay, Siân Cox:
  Improving the Reliability of Decision Tree and Naive Bayes Learners. 459-462
  
• Jinze Liu, Karl Strohmaier, Wei Wang:
  Revealing True Subspace Clusters in High Dimensions. 463-466
  
• Daoying Ma, Aidong Zhang:
  An Adaptive Density-Based Clustering Algorithm for Spatial Database with Noise. 467-470
  
• Xi Ma, HweeHwa Pang, Kian-Lee Tan:
  Finding Constrained Frequent Episodes Using Minimal Occurrences. 471-474
  
• Sandeep Mane, Jaideep Srivastava, San-Yih Hwang, Jamshid A. Vayghan:
  Estimation of False Negatives in Classification. 475-478
  
• Sameep Mehta, Srinivasan Parthasarathy, Hui Yang:
  Correlation Preserving Discretization. 479-482
  
• Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney:
  Active Feature-Value Acquisition for Classifier Induction. 483-486
  
• Da Meng, Krishnamoorthy Sivakumar, Hillol Kargupta:
  Privacy-Sensitive Bayesian Network Parameter Learning. 487-490
  
• Jia-Yu Pan, Hyung-Jeong Yang, Christos Faloutsos:
  MMSS: Multi-Modal Story-Oriented Video Summarization. 491-494
  
• Cheong Hee Park, Haesun Park, Panos M. Pardalos:
  A Comparative Study of Linear and Nonlinear Feature Extraction Methods. 495-498
  
• François Poulet:
  SVM and Graphical Algorithms: A Cooperative Approach. 499-502
  
• Dongmei Ren, Baoying Wang, William Perrizo:
  RDF: A Density-Based Outlier Detection Method using Vertical Data Representation. 503-506
  
• Ulrich Rückert, Lothar Richter, Stefan Kramer:
  Quantitative Association Rules Based on Half-Spaces: An Optimization Approach. 507-510
  
• Marko Salmenkivi:
  Evaluating Attraction in Spatial Point Patterns with an Application in the Field of Cultural History. 511-514
  
• Dawit Yimam Seid, Sharad Mehrotra:
  Efficient Relationship Pattern Mining Using Multi-Relational Iceberg-Cubes. 515-518
  
• Yi-Dong Shen, Zhiyong Shen, Shi-Ming Zhang, Qiang Yang:
  Cluster Cores-Based Clustering for High Dimensional Data. 519-522
  
• Dan A. Simovici, Namita Singla, Michael Kuperberg:
  Metric Incremental Clustering of Nominal Data. 523-526
  
• Nenad Stojanovic:
  n Ranking Refinements in the Step-by-Step Searching through a Product Catalogue. 527-530
  
• Jiang Su, Harry Zhang:
  Learning Conditional Independence Tree for Ranking. 531-534
  
• Jian-Tao Sun, Zheng Chen, Hua-Jun Zeng, Yuchang Lu, Chun-Yi Shi, Wei-Ying Ma:
  Supervised Latent Semantic Indexing for Document Categorization. 535-538
  
• Ping Sun:
  Sparse Kernel Least Squares Classifier. 539-542
  
• Alexandre Termier, Marie-Christine Rousset, Michèle Sebag:
  DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases. 543-546
  
• Andrei L. Turinsky, Robert L. Grossman:
  A Greedy Algorithm for Selecting Models in Ensembles. 547-550
  
• Juan D. Velásquez, Alejandro Bassi, Hiroshi Yasuda, Terumasa Aoki:
  Mining Web Data to Create Online Navigation Recommendations. 551-554
  
• Véronique Ventos, Henry Soldano, Thibaut Lamadon:
  Alpha Galois Lattices. 555-558
  
• Jiong Yang, Wei Wang:
  AGILE: A General Approach to Detect Transitions in Evolving Data Streams. 559-562
  
• Hwanjo Yu, Duane Searsmith, Xiaolei Li, Jiawei Han:
  Scalable Construction of Topic Directory with Nonparametric Closed Termset Mining. 563-566
  
• Harry Zhang, Shengli Sheng:
  Learning Weighted Naive Bayes with Accurate Ranking. 567-570
  
• Jianping Zhang, Eric Bloedorn, Lowell Rosen, Daniel Venese:
  Learning Rules from Highly Unbalanced Data Sets. 571-574
  
• Ning Zhong, Chunnian Liu, Yiyu Yao, Muneaki Ohshima, Mingxin Huang, Jiajin Huang:
  Relational Peculiarity Oriented Data Mining. 575-578