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ORCID7th ICDM 2007: Omaha, Nebraska, USA
- Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA. IEEE Computer Society 2007, ISBN 0-7695-3018-4
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, Xiang-Sun 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 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 Jr., 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 S. 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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