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Home > Conference > ICDM'07 Program

IEEE ICDM 2007 Program:

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Oct 29 10:30-12:00
Matrix Theoretic Methods
L DM463: Rong Liu and Yong Shi, "Succinct Matrix Approximation and Efficient k-NN Classification"
L DM718: Zhongyuan Zhang, Tao Li, Chris Ding, and Xiang-Sun Zhang, "Binary Matrix Factorization with Applications"
S DM714: Tao Li, Chris Ding, and Michael Jordan, "Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization"
S DM328: Dragomir Yankov, Eamonn Keogh, and Kin Kan, "Locally Constrained Support Vector Clustering"

Oct 29 10:30-12:00
Association Rules
L DM681: Axel Blumenstock, Franz Schweiggert, and Markus Müller, "Rule Cubes for Causal Investigations"
L DM764: Albrecht Zimmermann and Björn Bringmann, "The Chosen Few: On Identifying Valuable Patterns"
S DM524: Yan Zhang and Xindong Wu, "Noise Modelling with Associative Corruption Rules"
S DM650: Gemma Garriga, Hannes Heikinheimo, and Jouni Seppänen, "Cross-mining binary and numerical attributes"

Oct 29 10:30-12:00
Recommender Systems & Collaborative Filtering
L DM362: Tianyi Jiang and Alexander Tuzhilin, "Dynamic Micro Targeting: Fitness-Based Approach to Predicting Individual Preferences"
L DM582: Robert Bell and Yehuda Koren, "Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights"
S DM433: Ming Jia, Shaozhi Ye, Xing Li, and Julie Dickerson, "Web Site Recommendation Using HTTP Traffic"
S DM713: Haibin Cheng, Pang-Ning Tan, Sticklen Jon, and William F. Punch, "Recommendation via Query Centered Random Walk on K-partite Graph"

Oct 29 10:30-12:00
Sampling
L DM482: Feng Pan, Adam Roberts, Leonard McMillan, Fernando Pardo Manuel de Villena, David Threadgill, and Wei Wang, "Sample Selection for Maximal Diversity"
L DM571: Benjamin Arai, Song Lin, and Dimitrios Gunopulos, "Efficient Data Sampling in Heterogenous Peer-to-Peer Networks"
S DM299: Chedy Raïssi and Pascal Poncelet, "Sampling for Sequential Pattern Mining : From Static Databases to Data Streams"
S DM750: Xingquan Zhu, "Lazy Bagging for Classifying Imbalanced Data"

Oct 29 13:30-15:30
Data Streams
L DM581: Jing Gao, Wei Fan, and Jiawei Han, "On Appropriate Assumptions to Mine Data Streams"
L DM741: Toon Calders, Nele Dexters, and Bart Goethals, "Mining Frequent Itemsets in a Stream"
S DM245: QI HE, Kuiyu Chang, and Ee-Peng Lim, "Using Burstiness to Improve Clustering of Topics in News Streams"
S DM249: Ho Jin Woo and Won Suk Lee, "estMax: Finding maximal frequent itemsets over online data streams"
S DM324: Qi Zhang, Jinze Liu, and Wei Wang, "Incremental Subspace Clustering over Multiple Data Streams"
S DM383: Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, "Active Learning from Data Streams"

Oct 29 13:30-15:30
Probabilistic Models
L DM417: Liang Xiong, Fei Wang, and Changshui Zhang, "Multilevel Belief Propagation for Fast Inference on Markov Random Fields"
L DM774: Chao Wang, Venu Satuluri, and Srinivasan Parthasarathy, "Local Probabilistic Models for Link Prediction"
S DM443: Atsuhiro Takasu, Daiji Fukagawa, and Tatsuya Akutsu, "Statistical Learning Algorithm for Tree Similarity"
S DM699: Alexander Hinneburg, Andre Gohr, and Hans-Henning Gabriel, "Bayesian Folding-In with Dirichlet Kernels for PLSI"
S DM721: Arindam Banerjee and Hanhuai Shan, "Latent Dirichlet Conditional Naive-Bayes Models"
S DM789: Han-Shen Huang, Yu-Ming Chang, and Chun-Nan Hsu, "Training Conditional Random Fields by Periodic Step Size Adaptation"

Oct 29 13:30-15:30
Mining in Networked Settings I
L DM222: Jie Tang, Duo Zhang, and Limin Yao, "Social Network Extraction of Academic Researchers"
L DM271: Bo Long, Xiaoyun Xu, Zhongfei Zhang, and Philip S. Yu, "Community Learning by Graph Approximation"
S DM211: Ding Zhou, Sergey Orshanskiy, Hongyuan Zha, and C. Lee Giles, "Co-Ranking Authors and Documents in a Heterogeneous Network"
S DM674: BI CHEN, Qiankun Zhao, Bingjun Sun, and Prasenjit Mitra, "Temporal And Social Network Based Blogging Behavior Prediction In BlogSpace"
S DM702: Jianhua Ruan and Weixiong Zhang, "An Efficient Spectral Algorithm for Network Community Discovery and Its Applications to Biological and Social Networks"
S DM738: Jerry Scripps, Pang-Ning Tan, and Abdol-Hossein Esfahanian, "Exploration of Link Structure and Community-based Node Roles in Network"

Oct 29 16:00-17:30
Theory & Foundations
L DM206: Ruoming Jin, Yuri Breitbart, and Chibuike Muoh, "Data Discretization Unification"
L DM689: Deng Cai, "A Unified Approach for Sparse Subspace Learning"
S DM335: Biswanath Panda, Mirek Riedewald, Johannes Gehrke, and Stephen Pope, "High-Speed Function Approximation"
S DM630: Srivatsan Laxman, Prasad Naldurg, Raja Sripada, and Ramarathnam Venkatesan, "Connections between mining frequent itemsets and learning generative models"

Oct 29 16:00-17:30
Time Series
L DM327: Dragomir Yankov, Eamonn Keogh, and Umaa Rebbapragada, "Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets"
L DM728: Xiaozhe Wang, Anthony Wirth, and Liang Wang, "Structure-based Statistical Features and Multivariate Time Series Clustering"
S DM766: Tsuyoshi Ide, Spiros Papadimitriou, and Michail Vlachos, "Computing Correlation Anomaly Scores using Stochastic Nearest Neighbors"
S DM773: Yoshinobu Kawahara, Takehisa Yairi, and Kazuo Machida, "Change-Point Detection in Time-Series Data based on Subspace Identification"

Oct 29 16:00-17:30
Novelty, Outliers & Extensions
L DM207: Shin Ando, "Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection"
L DM576: Yixin Chen, Henry Bart, Xin Dang, and Hanxiang Peng, "Depth-Based Novelty Detection and its Application to Taxonomic Research"
S DM243: Gert Van Dijck, Marc Van Hulle, and Jo Van Vaerenbergh, "A Novel Criterion for Onset Detection: Differential Information Redundancy with Application to Human Movement Initiation"
S DM769: Mete Celik, James Kang, and Shashi Shekhar, "Zonal Co-location Pattern Discovery with Dynamic Parameters"

Oct 30 10:30-12:00
Applications
L DM494: Shing-Kit CHAN, Wai LAM, and Xiaofeng YU, "A Cascaded Approach to Biomedical Named Entity Recognition Using a Unified Model"
S DM278: Yinglung Liang, Yanyong Zhang, Hui Xiong, Ramendra Sahoo, and Anand Sivasubramaniam, "Failure Prediction in IBM BlueGene/L DMEvent Logs"
S DM461: Calum Robertson, Shlomo Geva, and Rodney Wolff, "Can the Content of Public Information be used to Forecast Abnormal Stock Market Behaviour?"
S DM476: Xiaoli Fern, Chaitanya Komireddy, and Margaret Burnett, "Mining Interpretable Human Strategies: A Case Study"
S DM525: David Kaplan and David Blei, "A Computational Approach to Style in American Poetry"

Oct 30 10:30-12:00
Text Mining I
L DM638: Sumeet Agarwal, Shantanu Godbole, Diwakar Punjani, and Shourya Roy, "How Much Noise is too Much: A Study in Automatic Text Classification"
L DM695: Richard C. Wang and William Cohen, "Language-Independent Set Expansion of Named Entities using the Web"
S DM567: Xuerui Wang, Andrew McCallum, and Xing Wei, "Topical N-grams: Phrase and Topic Discovery, with an Application to Information Retrieval"
S DM628: Ronen Feldman, Moshe Fresko, Jacob Goldenberg, Oded Netzer, Lyle Ungar, "Extracting Product Comparisons from Discussion Boards"

Oct 30 10:30-12:00
Graph Mining
L DM358: Mohammad Hasan, Vineet Chaoji, Saeed Salem, jeremy Besson, and Mohammed Zaki, "ORIGAMI: Mining Representative Orthogonal Graph Patterns"
L DM692: Huahai He and Ambuj Singh, "Efficient Algorithms for Mining Significant Substructures in Graphs with Quality Guarantees"
S DM208: Ruoming Jin, Scott Mccalle, and Eivind Almaas, "Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks"
S DM434: CHEN CHEN, Xifeng Yan, Feida Zhu, and Jiawei Han, "gApprox: Mining Frequent Approximate Patterns from a Massive Network"

Oct 30 13:30-15:00
Classifiers
L DM703: David Cieslak and Nitesh Chawla, "Detecting Fractures in Classifier Performance"
S DM374: Pannagadatta Shivaswamy, Wei Chu, and Martin Jansche, "A Support Vector Approach to Censored Targets"
S DM659: Frederik Janssen and Johannes Fürnkranz, "On Meta-Learning Rule Learning Heuristics"
S DM502: Florian Verhein and Sanjay Chawla, "Using Significant, Positively and Relatively Class Correlated Rules For Associative Classification of Imbalanced Datasets"
S DM739: Muhammad Subianto and Arno Siebes, "Understanding Discrete Classifiers - with a case study in gene prediction"

Oct 30 13:30-15:00
Sequences and Sequential Mining
S DM281: Feida Zhu, Xifeng Yan, Jiawei Han, and Philip S. Yu, "Efficient Discovery of Frequent Approximate Sequential Patterns"
S DM331: Longin Jan Latecki, Qiang Wang, Suzan Koknar-Tezel, and Vasileios Megalooikonomou, "Optimal Subsequence Bijection"
S DM360: Karam Gouda, Mosab Hassaan, and Mohammed Zaki, "PRISM: A Primal Approach for Frequent Sequence Mining"
S DM572: David Minnen, Thad Starner, Charles Isbell, and Irfan Essa, "Detecting Subdimensional Motifs: An Efficient Algorithm for Generalized Multivariate Pattern Discovery"

Oct 31 13:30-15:30
Clustering
L DM288: Junjie Wu, Hui Xiong, and Jian Chen, "A Generalization of Proximity Functions for K-means"
L DM338: Ying Cui, Xiaoli Fern, and Jennifer Dy, "Non-redundant Multi-view Clustering Via Orthogonalization"
L DM364: YANHUA CHEN, MANJEET REGE, and MING DONG, "Incorporating User provided Constraints into Document Clustering"
S DM691: Ira Assent, Ralph Krieger, Emmanuel Müller, and Thomas Seidl, "DUSC: Dimensionality Unbiased Subspace Clustering"
S DM726: Nam Nguyen and Rich Caruana, "Consensus Clustering"

Oct 31 13:30-15:30
Text Mining II
L DM466: Pu Wang and Lijun Chen, "Improving Text Classification by Using Encyclopedia Knowledge"
L DM506: Wei Jin, hung-hay ho, and Xin Wu, "Improving Knowledge Discovery by Combining Text Mining and Link Analysis Techniques"
S DM391: Nitin Jindal and Bing Liu, "Analyzing and Detecting Review Spam"
S DM402: Weizhu CHEN, "Document Transformation for Multi-label Feature Selection in Text Categorization"
S DM430: Sujeevan Aseervatham, Emmanuel Viennet, and Younès Bennani, "A Semantic Kernel for Semi-Structured Documents"
S DM513: Wen Pu and Ning Liu, "Local Word Bag Model for Text Categorization"

Oct 31 13:30-15:30
Frequent Patterns
L DM388: Ardian Kristanto Poernomo and Vivekanand Gopalkrishnan, "Mining statistical information of frequent fault-tolerant patterns in transactional databases"
L DM408: Claudio Lucchese, Salvatore Orlando, and Raffaele Perego, "Parallel Mining of Frequent Closed Patterns:Harnessing Modern Computer Architectures"
L DM470: Nikolaj Tatti, "Maximum Entropy Based Significance of Itemsets"
S DM407: Hassan Malik and John Kender, "Optimizing Frequency Queries for Data Mining Applications"
S DM735: Qian Wan and Aijun An, "Transitional Patterns and Their Significant Milestones"

Oct 31 16:00-18:00
Mining in Networked Settings II
L DM284: Brett Bader, Richard Harshman, and Tamara Kolda, "Temporal analysis of semantic graphs using ASALSAN"
L DM584: Vasileios Kandylas, S. Phineas Upham, and Lyle H. Ungar, "Finding cohesive clusters for analyzing knowledge communities"
L DM485: Daniele Quercia, Stephen Hailes, and Licia Capra, "Lightweight Distributed Trust Propagation"
S DM452: Ding Zhou, Isaac Councill, Hongyuan Zha, and C. Lee Giles, "Discovering Temporal Communities from Social Network Documents"
S DM586: Masoud Makrehchi and Mohamed Kamel, "A Text Classification Framework with a Local Feature Ranking for Learning Social Networks"

Oct 31 16:00-18:00
New Learning Formulations
L DM736: David Musicant, Janara Christensen, and Jamie Olson, "Supervised Learning by Training on Aggregate Outputs"
S DM480: Shen-Shyang Ho and Roman Polyak, "Confident Identification of Relevant Objects Based on Nonlinear Rescaling Method and Transductive Inference"
S DM515: Chris Bourke, Kun Deng, Stephen Scott, and Julie Sunderman, "Bandit-Based Algorithms for Budgeted Learning"
S DM548: Pinata Winoto, Yiu-ming Cheung, and Jiming Liu, "Mechanism Design for Clustering Aggregation by Selfish Systems"
S DM631: Jilles Vreeken, Matthijs van Leeuwen, and Arno Siebes, "Preserving Privacy through Data Generation"
S DM779: Ruizhang Huang and Wai LAM, "Semi-supervised Document Clustering via Active Learning with Pairwise Constraints"

Oct 31 16:00-18:00
Statistical Methods
L DM406: Dacheng Tao, Xuelong Li, Xindong Wu, and Stephen Maybank, "GMDA: General Averaged Divergences Analysis"
L DM442: Xiaoming Liu, Jianwei Yin, Zhilin Feng, and Jinxiang Dong, "A Pairwise Covariance-preserving Projection Method for Dimension Reduction"
S DM446: Suhrid Balakrishnan and David Madigan, "Finding Predictive Runs with LAPS"
S DM477: Deng Cai, "Efficient Kernel Discriminant Analysis via Spectral Regression"
S DM533: Yang Yu, Zhi-Hua Zhou, and Kai Ming Ting, "Cocktail Ensemble for Regression"
S DM697: Jing Peng and Stefan Robila, "Weighted Additive Criterion for Linear Dimension Reduction"

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