7. ICDM 2007: Omaha, Nebraska, USA

Regular Papers

• Sumeet Agarwal, Shantanu Godbole, Diwakar Punjani, Shourya Roy:
  How Much Noise Is Too Much: A Study in Automatic Text Classification. 3-12
  
• Shin Ando:
  Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection. 13-22
  
• Benjamin Arai, Song Lin, Dimitrios Gunopulos:
  Efficient Data Sampling in Heterogeneous Peer-to-Peer Networks. 23-32
  
• Brett W. Bader, Richard A. Harshman, Tamara G. Kolda:
  Temporal Analysis of Semantic Graphs Using ASALSAN. 33-42
  
• Robert M. Bell, Yehuda Koren:
  Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights. 43-52
  
• Axel Blumenstock, Franz Schweiggert, Markus Müller:
  Rule Cubes for Causal Investigations. 53-62
  
• Björn Bringmann, Albrecht Zimmermann:
  The Chosen Few: On Identifying Valuable Patterns. 63-72
  
• Deng Cai, Xiaofei He, Jiawei Han:
  Spectral Regression: A Unified Approach for Sparse Subspace Learning. 73-82
  
• Toon Calders, Nele Dexters, Bart Goethals:
  Mining Frequent Itemsets in a Stream. 83-92
  
• Shing-Kit Chan, Wai Lam, Xiaofeng Yu:
  A Cascaded Approach to Biomedical Named Entity Recognition Using a Unified Model. 93-102
  
• Yanhua Chen, Manjeet Rege, Ming Dong, Jing Hua:
  Incorporating User Provided Constraints into Document Clustering. 103-112
  
• Yixin Chen, Henry L. Bart Jr., Xin Dang, Hanxiang Peng:
  Depth-Based Novelty Detection and Its Application to Taxonomic Research. 113-122
  
• David A. Cieslak, Nitesh V. Chawla:
  Detecting Fractures in Classifier Performance. 123-132
  
• Ying Cui, Xiaoli Z. Fern, Jennifer G. Dy:
  Non-redundant Multi-view Clustering via Orthogonalization. 133-142
  
• Jing Gao, Wei Fan, Jiawei Han:
  On Appropriate Assumptions to Mine Data Streams: Analysis and Practice. 143-152
  
• Mohammad Al Hasan, Vineet Chaoji, Saeed Salem, Jérémy Besson, Mohammed Javeed Zaki:
  ORIGAMI: Mining Representative Orthogonal Graph Patterns. 153-162
  
• Huahai He, Ambuj K. Singh:
  Efficient Algorithms for Mining Significant Substructures in Graphs with Quality Guarantees. 163-172
  
• Tianyi Jiang, Alexander Tuzhilin:
  Dynamic Micro Targeting: Fitness-Based Approach to Predicting Individual Preferences. 173-182
  
• Ruoming Jin, Yuri Breitbart, Chibuike Muoh:
  Data Discretization Unification. 183-192
  
• Wei Jin, Rohini K. Srihari, Hung Hay Ho, Xin Wu:
  Improving Knowledge Discovery in Document Collections through Combining Text Retrieval and Link Analysis Techniques. 193-202
  
• Vasileios Kandylas, S. Phineas Upham, Lyle H. Ungar:
  Finding Cohesive Clusters for Analyzing Knowledge Communities. 203-212
  
• Rong Liu, Yong Shi:
  Succinct Matrix Approximation and Efficient k-NN Classification. 213-222
  
• Xiaoming Liu, Zhaohui Wang, Zhilin Feng, Jinshan Tang:
  A Pairwise Covariance-Preserving Projection Method for Dimension Reduction. 223-231
  
• Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip S. Yu:
  Community Learning by Graph Approximation. 232-241
  
• Claudio Lucchese, Salvatore Orlando, Raffaele Perego:
  Parallel Mining of Frequent Closed Patterns: Harnessing Modern Computer Architectures. 242-251
  
• David R. Musicant, Janara M. Christensen, Jamie F. Olson:
  Supervised Learning by Training on Aggregate Outputs. 252-261
  
• Feng Pan, Adam Roberts, Leonard McMillan, David Threadgill, Wei Wang:
  Sample Selection for Maximal Diversity. 262-271
  
• Ardian Kristanto Poernomo, Vivekanand Gopalkrishnan:
  Mining Statistical Information of Frequent Fault-Tolerant Patterns in Transactional Databases. 272-281
  
• Daniele Quercia, Stephen Hailes, Licia Capra:
  Lightweight Distributed Trust Propagation. 282-291
  
• Jie Tang, Duo Zhang, Limin Yao:
  Social Network Extraction of Academic Researchers. 292-301
  
• Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Maybank:
  General Averaged Divergence Analysis. 302-311
  
• Nikolaj Tatti:
  Maximum Entropy Based Significance of Itemsets. 312-321
  
• Chao Wang, Venu Satuluri, Srinivasan Parthasarathy:
  Local Probabilistic Models for Link Prediction. 322-331
  
• Pu Wang, Jian Hu, Hua-Jun Zeng, Lijun Chen, Zheng Chen:
  Improving Text Classification by Using Encyclopedia Knowledge. 332-341
  
• Richard C. Wang, William W. Cohen:
  Language-Independent Set Expansion of Named Entities Using the Web. 342-350
  
• Xiaozhe Wang, Anthony Wirth, Liang Wang:
  Structure-Based Statistical Features and Multivariate Time Series Clustering. 351-360
  
• Junjie Wu, Hui Xiong, Jian Chen, Wenjun Zhou:
  A Generalization of Proximity Functions for K-Means. 361-370
  
• Liang Xiong, Fei Wang, Changshui Zhang:
  Multilevel Belief Propagation for Fast Inference on Markov Random Fields. 371-380
  
• Dragomir Yankov, Eamonn J. Keogh, Umaa Rebbapragada:
  Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets. 381-390
  
• Zhongyuan Zhang, Tao Li, Chris H. Q. Ding, Xiangsun Zhang:
  Binary Matrix Factorization with Applications. 391-400
  

Short Papers

• Sujeevan Aseervatham, Emmanuel Viennet, Younès Bennani:
  A Semantic Kernel for Semi-structured DocumentS. 403-408
  
• Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
  DUSC: Dimensionality Unbiased Subspace Clustering. 409-414
  
• Suhrid Balakrishnan, David Madigan:
  Finding Predictive Runs with LAPS. 415-420
  
• Arindam Banerjee, Hanhuai Shan:
  Latent Dirichlet Conditional Naive-Bayes Models. 421-426
  
• Deng Cai, Xiaofei He, Jiawei Han:
  Efficient Kernel Discriminant Analysis via Spectral Regression. 427-432
  
• Mete Celik, James M. Kang, Shashi Shekhar:
  Zonal Co-location Pattern Discovery with Dynamic Parameters. 433-438
  
• Bi Chen, Qiankun Zhao, Bingjun Sun, Prasenjit Mitra:
  Predicting Blogging Behavior Using Temporal and Social Networks. 439-444
  
• Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han:
  gApprox: Mining Frequent Approximate Patterns from a Massive Network. 445-450
  
• Weizhu Chen, Jun Yan, Benyu Zhang, Zheng Chen, Qiang Yang:
  Document Transformation for Multi-label Feature Selection in Text Categorization. 451-456
  
• Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William F. Punch:
  Recommendation via Query Centered Random Walk on K-Partite Graph. 457-462
  
• Kun Deng, Chris Bourke, Stephen D. Scott, Julie Sunderman, Yaling Zheng:
  Bandit-Based Algorithms for Budgeted Learning. 463-468
  
• Ronen Feldman, Moshe Fresko, Jacob Goldenberg, Oded Netzer, Lyle H. Ungar:
  Extracting Product Comparisons from Discussion Boards. 469-474
  
• Xiaoli Z. Fern, Chaitanya Komireddy, Margaret M. Burnett:
  Mining Interpretable Human Strategies: A Case Study. 475-480
  
• Gemma C. Garriga, Hannes Heikinheimo, Jouni K. Seppänen:
  Cross-Mining Binary and Numerical Attributes. 481-486
  
• Karam Gouda, Mosab Hassaan, Mohammed Javeed Zaki:
  Prism: A Primal-Encoding Approach for Frequent Sequence Mining. 487-492
  
• Qi He, Kuiyu Chang, Ee-Peng Lim:
  Using Burstiness to Improve Clustering of Topics in News Streams. 493-498
  
• Alexander Hinneburg, Hans-Henning Gabriel, André Gohr:
  Bayesian Folding-In with Dirichlet Kernels for PLSI. 499-504
  
• Shen-Shyang Ho, Roman A. Polyak:
  Confident Identification of Relevant Objects Based on Nonlinear Rescaling Method and Transductive Inference. 505-510
  
• Han-Shen Huang, Yu-Ming Chang, Chun-Nan Hsu:
  Training Conditional Random Fields by Periodic Step Size Adaptation for Large-Scale Text Mining. 511-516
  
• Ruizhang Huang, Wai Lam:
  Semi-supervised Document Clustering via Active Learning with Pairwise Constraints. 517-522
  
• Tsuyoshi Idé, Spiros Papadimitriou, Michail Vlachos:
  Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors. 523-528
  
• Frederik Janssen, Johannes Fürnkranz:
  On Meta-Learning Rule Learning Heuristics. 529-534
  
• Ming Jia, Shaozhi Ye, Xing Li, Julie A. Dickerson:
  Web Site Recommendation Using HTTP Traffic. 535-540
  
• Ruoming Jin, Scott McCallen, Eivind Almaas:
  Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks. 541-546
  
• Nitin Jindal, Bing Liu:
  Analyzing and Detecting Review Spam. 547-552
  
• David M. Kaplan, David M. Blei:
  A Computational Approach to Style in American Poetry. 553-558
  
• Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida:
  Change-Point Detection in Time-Series Data Based on Subspace Identification. 559-564
  
• Longin Jan Latecki, Qiang Wang, Suzan Köknar-Tezel, Vasileios Megalooikonomou:
  Optimal Subsequence Bijection. 565-570
  
• Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ramarathnam Venkatesan:
  Connections between Mining Frequent Itemsets and Learning Generative Models. 571-576
  
• Tao Li, Chris H. Q. Ding, Michael I. Jordan:
  Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization. 577-582
  
• Yinglung Liang, Yanyong Zhang, Hui Xiong, Ramendra K. Sahoo:
  Failure Prediction in IBM BlueGene/L Event Logs. 583-588
  
• Masoud Makrehchi, Mohamed S. Kamel:
  A Text Classification Framework with a Local Feature Ranking for Learning Social Networks. 589-594
  
• Hassan H. Malik, John R. Kender:
  Optimizing Frequency Queries for Data Mining Applications. 595-600
  
• David Minnen, Charles L. Isbell, Irfan A. Essa, Thad Starner:
  Detecting Subdimensional Motifs: An Efficient Algorithm for Generalized Multivariate Pattern Discovery. 601-606
  
• Nam Nguyen, Rich Caruana:
  Consensus Clusterings. 607-612
  
• Biswanath Panda, Mirek Riedewald, Johannes Gehrke, Stephen B. Pope:
  High-Speed Function Approximation. 613-618
  
• Jing Peng, Stefan A. Robila:
  Weighted Additive Criterion for Linear Dimension Reduction. 619-624
  
• Wen Pu, Ning Liu, Shuicheng Yan, Jun Yan, Kunqing Xie, Zheng Chen:
  Local Word Bag Model for Text Categorization. 625-630
  
• Chedy Raïssi, Pascal Poncelet:
  Sampling for Sequential Pattern Mining: From Static Databases to Data Streams. 631-636
  
• Calum Robertson, Shlomo Geva, Rodney C. Wolff:
  Can the Content of Public News Be Used to Forecast Abnormal Stock Market Behaviour? 637-642
  
• Jianhua Ruan, Weixiong Zhang:
  An Efficient Spectral Algorithm for Network Community Discovery and Its Applications to Biological and Social Networks. 643-648
  
• Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian:
  Exploration of Link Structure and Community-Based Node Roles in Network Analysis. 649-654
  
• Pannagadatta K. Shivaswamy, Wei Chu, Martin Jansche:
  A Support Vector Approach to Censored Targets. 655-660
  
• Muhammad Subianto, Arno Siebes:
  Understanding Discrete Classifiers with a Case Study in Gene Prediction. 661-666
  
• Atsuhiro Takasu, Daiji Fukagawa, Tatsuya Akutsu:
  Statistical Learning Algorithm for Tree Similarity. 667-672
  
• Gert Van Dijck, Marc M. Van Hulle, Jo Van Vaerenbergh:
  A Novel Criterion for Onset Detection: Differential Information Redundancy with Application to Human Movement Initiation. 673-678
  
• Florian Verhein, Sanjay Chawla:
  Using Significant, Positively Associated and Relatively Class Correlated Rules for Associative Classification of Imbalanced Datasets. 679-684
  
• Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes:
  Preserving Privacy through Data Generation. 685-690
  
• Qian Wan, Aijun An:
  Transitional Patterns and Their Significant Milestones. 691-696
  
• Xuerui Wang, Andrew McCallum, Xing Wei:
  Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval. 697-702
  
• Pinata Winoto, Yiu-ming Cheung, Jiming Liu:
  Mechanism Design for Clustering Aggregation by Selfish Systems. 703-708
  
• Ho Jin Woo, Won Suk Lee:
  estMax: Tracing Maximal Frequent Itemsets over Online Data Streams. 709-714
  
• Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan:
  Locally Constrained Support Vector Clustering. 715-720
  
• Yang Yu, Zhi-Hua Zhou, Kai Ming Ting:
  Cocktail Ensemble for Regression. 721-726
  
• Qi Zhang, Jinze Liu, Wei Wang:
  Incremental Subspace Clustering over Multiple Data Streams. 727-732
  
• Yan Zhang, Xindong Wu:
  Noise Modeling with Associative Corruption Rules. 733-738
  
• Ding Zhou, Sergey A. Orshanskiy, Hongyuan Zha, C. Lee Giles:
  Co-ranking Authors and Documents in a Heterogeneous Network. 739-744
  
• Ding Zhou, Isaac G. Councill, Hongyuan Zha, C. Lee Giles:
  Discovering Temporal Communities from Social Network Documents. 745-750
  
• Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu:
  Efficient Discovery of Frequent Approximate Sequential Patterns. 751-756
  
• Xingquan Zhu, Peng Zhang, Xiaodong Lin, Yong Shi:
  Active Learning from Data Streams. 757-762
  
• Xingquan Zhu:
  Lazy Bagging for Classifying Imbalanced Data. 763-768
  

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