9. ICDM 2009: Miami, Florida, USA

Regular Papers

• Deepak Agarwal, Bee-Chung Chen, Pradheep Elango:
  Explore/Exploit Schemes for Web Content Optimization. 1-10
  
• Nitin Agarwal, Huan Liu, Shankara B. Subramanya, John J. Salerno, Philip S. Yu:
  Connecting Sparsely Distributed Similar Bloggers. 11-20
  
• Timo Aho, Bernard Zenko, Saso Dzeroski:
  Rule Ensembles for Multi-target Regression. 21-30
  
• Kanishka Bhaduri, Ashok N. Srivastava:
  A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks. 31-40
  
• Indrajit Bhattacharya, Shantanu Godbole, Sachindra Joshi, Ashish Verma:
  Cross-Guided Clustering: Transfer of Relevant Supervision across Domains for Improved Clustering. 41-50
  
• Forrest Briggs, Raviv Raich, Xiaoli Z. Fern:
  Audio Classification of Bird Species: A Statistical Manifold Approach. 51-60
  
• Andrea Campagna, Rasmus Pagh:
  Finding Associations and Computing Similarity via Biased Pair Sampling. 61-70
  
• Guangyun Chen, Gang Chen, Jianwen Zhang, Shuo Chen, Changshui Zhang:
  Beyond Banditron: A Conservative and Efficient Reduction for Online Multiclass Prediction with Bandit Setting Model. 71-80
  
• Wei Cheng, Xiaoming Jin, Jian-Tao Sun:
  Probabilistic Similarity Query on Dimension Incomplete Data. 81-90
  
• Young-Rae Cho, Lei Shi, Aidong Zhang:
  flowNet: Flow-Based Approach for Efficient Analysis of Complex Biological Networks. 91-100
  
• Santanu Das, Kanishka Bhaduri, Nikunj C. Oza, Ashok N. Srivastava:
  ?-Anomica: A Fast Support Vector Based Novelty Detection Technique. 101-109
  
• Sandipan Dey, Vandana Pursnani Janeja, Aryya Gangopadhyay:
  Temporal Neighborhood Discovery Using Markov Models. 110-119
  
• Jun Du, Charles X. Ling:
  Active Learning with Generalized Queries. 120-128
  
• Avinava Dubey, Jinesh Machchhar, Chiranjib Bhattacharyya, Soumen Chakrabarti:
  Conditional Models for Non-smooth Ranking Loss Functions. 129-138
  
• Andrew Foss, Osmar R. Zaïane, Sandra Zilles:
  Unsupervised Class Separation of Multivariate Data through Cumulative Variance-Based Ranking. 139-148
  
• Qiang Fu, Jian-Guang Lou, Yi Wang, Jiang Li:
  Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis. 149-158
  
• Quanquan Gu, Jie Zhou:
  Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification. 159-168
  
• Michael Hay, Chao Li, Gerome Miklau, David Jensen:
  Accurate Estimation of the Degree Distribution of Private Networks. 169-178
  
• Shohei Hido, Hisashi Kashima:
  A Linear-Time Graph Kernel. 179-188
  
• Kaizhu Huang, Yiming Ying, Colin Campbell:
  GSML: A Unified Framework for Sparse Metric Learning. 189-198
  
• Lili Jiang, Jianyong Wang, Ning An, Shengyuan Wang, Jian Zhan, Lian Li:
  GRAPE: A Graph-Based Framework for Disambiguating People Appearances in Web Search. 199-208
  
• Ruoming Jin, Yuri Breitbart, Rong Li:
  A Tree-Based Framework for Difference Summarization. 209-218
  
• Toshihiro Kamishima, Masahiro Hamasaki, Shotaro Akaho:
  TrBagg: A Simple Transfer Learning Method and its Application to Personalization in Collaborative Tagging. 219-228
  
• U. Kang, Charalampos E. Tsourakakis, Christos Faloutsos:
  PEGASUS: A Peta-Scale Graph Mining System. 229-238
  
• Yiping Ke, James Cheng, Jeffrey Xu Yu:
  Efficient Discovery of Frequent Correlated Subgraph Pairs. 239-248
  
• Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl:
  Self-Adaptive Anytime Stream Clustering. 249-258
  
• Suzan Koknar-Tezel, Longin Jan Latecki:
  Improving SVM Classification on Imbalanced Data Sets in Distance Spaces. 259-267
  
• Liyun Li, Umut Topkara, Baris Coskun, Nasir D. Memon:
  CoCoST: A Computational Cost Efficient Classifier. 268-277
  
• Nan Li, Yang Yu, Zhi-Hua Zhou:
  Semi-naive Exploitation of One-Dependence Estimators. 278-287
  
• Kun Liu, Evimaria Terzi:
  A Framework for Computing the Privacy Scores of Users in Online Social Networks. 288-297
  
• Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou:
  Least Square Incremental Linear Discriminant Analysis. 298-306
  
• Xiaobai Liu, Shuicheng Yan, Jun Yan, Hai Jin:
  Unified Solution to Nonnegative Data Factorization Problems. 307-316
  
• Haibing Lu, Jaideep Vaidya, Vijayalakshmi Atluri, Yuan Hong:
  Extended Boolean Matrix Decomposition. 317-326
  
• Zhenyu Lu, Xindong Wu, Josh Bongard:
  Active Learning with Adaptive Heterogeneous Ensembles. 327-336
  
• Dijun Luo, Chris H. Q. Ding, Heng Huang, Tao Li:
  Non-negative Laplacian Embedding. 337-346
  
• Yasuko Matsubara, Yasushi Sakurai, Masatoshi Yoshikawa:
  Scalable Algorithms for Distribution Search. 347-356
  
• Martin Renqiang Min, David A. Stanley, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang:
  A Deep Non-linear Feature Mapping for Large-Margin kNN Classification. 357-366
  
• Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Shamlo:
  Finding Time Series Motifs in Disk-Resident Data. 367-376
  
• Emmanuel Müller, Ira Assent, Stephan Günnemann, Ralph Krieger, Thomas Seidl:
  Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data. 377-386
  
• Marion Neumann, Kristian Kersting, Zhao Xu, Daniel Schulz:
  Stacked Gaussian Process Learning. 387-396
  
• Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad:
  Evaluating Statistical Tests for Within-Network Classifiers of Relational Data. 397-406
  
• Debprakash Patnaik, Srivatsan Laxman, Naren Ramakrishnan:
  Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis. 407-416
  
• Nikos Pelekis, Ioannis Kopanakis, Evangelos E. Kotsifakos, Elias Frentzos, Yannis Theodoridis:
  Clustering Trajectories of Moving Objects in an Uncertain World. 417-427
  
• Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko Sadamasa, Koray Kavukcuoglu, Jason Weston:
  Semi-Supervised Sequence Labeling with Self-Learned Features. 428-437
  
• Matthew W. Robards, Peter Sunehag:
  Semi-Markov kMeans Clustering and Activity Recognition from Body-Worn Sensors. 438-446
  
• Ning Ruan, Ruoming Jin, Victor E. Lee, Kun Huang:
  A Sparsification Approach for Temporal Graphical Model Decomposition. 447-456
  
• Ted Sandler, Lyle H. Ungar, Koby Crammer:
  Resolving Identity Uncertainty with Learned Random Walks. 457-465
  
• Hanhuai Shan, Arindam Banerjee, Nikunj C. Oza:
  Discriminative Mixed-Membership Models. 466-475
  
• Kostyantyn M. Shchekotykhin, Gerhard Friedrich:
  Argumentation Based Constraint Acquisition. 476-482
  
• Yuan Shi, Zhen-zhong Lan, Wei Liu, Wei Bi:
  Extending Semi-supervised Learning Methods for Inductive Transfer Learning. 483-492
  
• Yizhou Sun, Jiawei Han, Jing Gao, Yintao Yu:
  iTopicModel: Information Network-Integrated Topic Modeling. 493-502
  
• Lei Tang, Xufei Wang, Huan Liu:
  Uncoverning Groups via Heterogeneous Interaction Analysis. 503-512
  
• Nikolaj Tatti:
  Significance of Episodes Based on Minimal Windows. 513-522
  
• Christian Thurau, Kristian Kersting, Christian Bauckhage:
  Convex Non-negative Matrix Factorization in the Wild. 523-532
  
• Deepak S. Turaga, Michail Vlachos, Olivier Verscheure:
  On K-Means Cluster Preservation Using Quantization Schemes. 533-542
  
• Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal Slovin:
  Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging. 543-551
  
• Fan Wang, Gagan Agrawal:
  Extracting Output Metadata from Scientific Deep Web Data Sources. 552-561
  
• Fei Wang, Xin Wang, Tao Li:
  Semi-supervised Multi-task Learning with Task Regularizations. 562-568
  
• Zhuang Wang, Slobodan Vucetic:
  Fast Online Training of Ramp Loss Support Vector Machines. 569-577
  
• Yun Xiong, Yangyong Zhu:
  Mining Peculiarity Groups in Day-by-Day Behavioral Datasets. 578-587
  
• Wei Xu, Ling Huang, Armando Fox, David Patterson, Michael I. Jordan:
  Online System Problem Detection by Mining Patterns of Console Logs. 588-597
  
• Jun Yan, Ning Liu, Shuicheng Yan, Qiang Yang, Zheng Chen:
  Synthesizing Novel Dimension Reduction Algorithms in Matrix Trace Oriented Optimization Framework. 598-606
  
• Jian Yang, Ning Zhong, Yiyu Yao, Jue Wang:
  Peculiarity Analysis for Classifications. 607-616
  
• Xiao Yu, Lu An Tang, Jiawei Han:
  Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection. 617-626
  
• Peng Zhang, Xingquan Zhu, Li Guo:
  Mining Data Streams with Labeled and Unlabeled Training Examples. 627-636
  
• Bin Zhao, James Tin-Yau Kwok, Changshui Zhang:
  Maximum Margin Clustering with Multivariate Loss Function. 637-646
  
• Wenjun Zhou, Hui Xiong:
  Efficient Discovery of Confounders in Large Data Sets. 647-656
  
• Xingquan Zhu, Xindong Wu, Chengqi Zhang:
  Vague One-Class Learning for Data Streams. 657-666
  
• Zeyuan Allen Zhu, Weizhu Chen, Chenguang Zhu, Gang Wang, Haixun Wang, Zheng Chen:
  Inverse Time Dependency in Convex Regularized Learning. 667-676
  
• Zeyuan Allen Zhu, Weizhu Chen, Gang Wang, Chenguang Zhu, Zheng Chen:
  P-packSVM: Parallel Primal grAdient desCent Kernel SVM. 677-686
  

Short Papers

• Anushka Anand, Leland Wilkinson, Dang Nhon Tuan:
  An L-infinity Norm Visual Classifier. 687-692
  
• Fabrizio Angiulli, Fabio Fassetti:
  Outlier Detection Using Inductive Logic Programming. 693-698
  
• Shenghua Bao, Shengliang Xu, Li Zhang, Rong Yan, Zhong Su, Dingyi Han, Yong Yu:
  Joint Emotion-Topic Modeling for Social Affective Text Mining. 699-704
  
• Mohsen Bayati, Margot Gerritsen, David Gleich, Amin Saberi, Ying Wang:
  Algorithms for Large, Sparse Network Alignment Problems. 705-710
  
• Wei Bian, Dacheng Tao:
  Dirichlet Mixture Allocation for Multiclass Document Collections Modeling. 711-715
  
• Peter Boyen, Frank Neven, Dries Van Dyck, Aalt-Jan van Dijk, Roeland C. H. J. van Ham:
  SLIDER: Mining Correlated Motifs in Protein-Protein Interaction Networks. 716-721
  
• Budhaditya Saha, Duc-Son Pham, Mihai Lazarescu, Svetha Venkatesh:
  Effective Anomaly Detection in Sensor Networks Data Streams. 722-727
  
• Markus Bundschus, Shipeng Yu, Volker Tresp, Achim Rettinger, Mathäus Dejori, Hans-Peter Kriegel:
  Hierarchical Bayesian Models for Collaborative Tagging Systems. 728-733
  
• Yuanzhe Cai, Gao Cong, Xu Jia, Hongyan Liu, Jun He, Jiaheng Lu, Xiaoyong Du:
  Efficient Algorithm for Computing Link-Based Similarity in Real World Networks. 734-739
  
• Rhonda Chaytor, Ke Wang, Patricia Brantingham:
  Fine-Grain Perturbation for Privacy Preserving Data Publishing. 740-745
  
• Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell:
  Accelerated Gradient Method for Multi-task Sparse Learning Problem. 746-751
  
• Guillaume Cleuziou, Matthieu Exbrayat, Lionel Martin, Jacques-Henri Sublemontier:
  CoFKM: A Centralized Method for Multiple-View Clustering. 752-757
  
• Debasish Das, Zoran Obradovic, Slobodan Vucetic:
  Active Selection of Sensor Sites in Remote Sensing Applications. 758-763
  
• Stijn De Saeger, Kentaro Torisawa, Jun'ichi Kazama, Kow Kuroda, Masaki Murata:
  Large Scale Relation Acquisition Using Class Dependent Patterns. 764-769
  
• Lian Duan, William Nick Street:
  Finding Maximal Fully-Correlated Itemsets in Large Databases. 770-775
  
• Qiang Fu, Arindam Banerjee:
  Bayesian Overlapping Subspace Clustering. 776-781
  
• Edgar González, Jordi Turmo:
  Unsupervised Relation Extraction by Massive Clustering. 782-787
  
• Mihajlo Grbovic, Slobodan Vucetic:
  Regression Learning Vector Quantization. 788-793
  
• Francesco Gullo, Carlotta Domeniconi, Andrea Tagarelli:
  Projective Clustering Ensembles. 794-799
  
• Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Yihong Gong:
  Knowledge Discovery from Citation Networks. 800-805
  
• Antonella Guzzo, Domenico Saccà, Edoardo Serra:
  An Effective Approach to Inverse Frequent Set Mining. 806-811
  
• Samson Hauguel, ChengXiang Zhai, Jiawei Han:
  Parallel PathFinder Algorithms for Mining Structures from Graphs. 812-817
  
• Anne Hendrikse, Luuk J. Spreeuwers, Raymond N. J. Veldhuis:
  A Bootstrap Approach to Eigenvalue Correction. 818-823
  
• Jing Jiang:
  Modeling Syntactic Structures of Topics with a Nested HMM-LDA. 824-829
  
• Deepti Joshi, Leen-Kiat Soh, Ashok Samal:
  Redistricting Using Heuristic-Based Polygonal Clustering. 830-835
  
• Jussi Kujala, Timo Aho, Tapio Elomaa:
  A Walk from 2-Norm SVM to 1-Norm SVM. 836-841
  
• Levi Lelis, Jörg Sander:
  Semi-supervised Density-Based Clustering. 842-847
  
• Dongyu Lin, Dean P. Foster:
  VIF Regression: A Fast Regression Algorithm for Large Data. 848-853
  
• Bin Liu, Shuo Chen, Mingjie Qian, Changshui Zhang:
  Sparse Norm-Regularized Reconstructive Coefficients Learning. 854-859
  
• Qingbao Liu, Guozhu Dong:
  A Contrast Pattern Based Clustering Quality Index for Categorical Data. 860-865
  
• Chong Long, Minlie Huang, Xiaoyan Zhu, Ming Li:
  Multi-document Summarization by Information Distance. 866-871
  
• Ian Molloy, Ninghui Li, Tiancheng Li:
  On the (In)Security and (Im)Practicality of Outsourcing Precise Association Rule Mining. 872-877
  
• Michinari Momma, Satoshi Morinaga, Daisuke Komura:
  Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning. 878-883
  
• Fabrice Muhlenbach, Stéphane Lallich:
  A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters. 884-889
  
• Sumit Negi, Sachindra Joshi, Anup Chalamalla, L. Venkata Subramaniam:
  Automatically Extracting Dialog Models from Conversation Transcripts. 890-895
  
• Viet-An Nguyen, Ee-Peng Lim, Jing Jiang, Aixin Sun:
  To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework. 896-901
  
• Miho Ohsaki, Masakazu Nakase, Shigeru Katagiri:
  Analysis of Subsequence Time-Series Clustering Based on Moving Average. 902-907
  
• Markus Ojala, Gemma C. Garriga:
  Permutation Tests for Studying Classifier Performance. 908-913
  
• Claudia Plant, Afra M. Wohlschlager, Andrew Zherdin:
  Interaction-Based Clustering of Multivariate Time Series. 914-919
  
• Ardian Kristanto Poernomo, Vivekanand Gopalkrishnan:
  PUB: A Class Description Technique Based on Partial Coverage of Subspace. 920-925
  
• Ali Mustafa Qamar, Éric Gaussier:
  Online and Batch Learning of Generalized Cosine Similarities. 926-931
  
• Jiangtao Qiu, Zhangxi Lin, Changjie Tang, Shaojie Qiao:
  Discovering Organizational Structure in Dynamic Social Network. 932-937
  
• Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine:
  Kernel Conditional Quantile Estimation via Reduction Revisited. 938-943
  
• Jiangtao Ren, Sau Dan Lee, Xianlu Chen, Ben Kao, Reynold Cheng, David Wai-Lok Cheung:
  Naive Bayes Classification of Uncertain Data. 944-949
  
• Céline Robardet:
  Constraint-Based Pattern Mining in Dynamic Graphs. 950-955
  
• Frank Rosenthal, Ulrike Fischer, Peter Benjamin Volk, Wolfgang Lehner:
  Global Slope Change Synopses for Measurement Maps. 956-961
  
• Dan Roth, Yuancheng Tu:
  Aspect Guided Text Categorization with Unobserved Labels. 962-967
  
• Jianhua Ruan:
  A Fully Automated Method for Discovering Community Structures in High Dimensional Data. 968-973
  
• Guy Shani, Christopher Meek, Asela Gunawardana:
  Hierarchical Probabilistic Segmentation of Discrete Events. 974-979
  
• Zhiyong Shen, Ping Luo, Yuhong Xiong, Jun Sun, Yidong Shen:
  Topic Modeling for Sequences of Temporal Activities. 980-985
  
• Adrian Silvescu, Cornelia Caragea, Vasant Honavar:
  Combining Super-Structuring and Abstraction on Sequence Classification. 986-991
  
• Carlos Nascimento Silla Jr., Alex Alves Freitas:
  A Global-Model Naive Bayes Approach to the Hierarchical Prediction of Protein Functions. 992-997
  
• Shamsher Singh, K. K. Biswas:
  Spatio-temporal Energy Based Gait Recognition. 998-1003
  
• Aaron M. Smalter, Jun Huan, Gerald H. Lushington:
  Feature Selection in the Tensor Product Feature Space. 1004-1009
  
• Jie Tang, Jing Zhang, Jeffrey Xu Yu, Zi Yang, Keke Cai, Rui Ma, Li Zhang, Zhong Su:
  Topic Distributions over Links on Web. 1010-1015
  
• Wei Tang, Zhengdong Lu, Inderjit S. Dhillon:
  Clustering with Multiple Graphs. 1016-1021
  
• Fei Wang, Jimeng Sun, Tao Li, Nikos Anerousis:
  Two Heads Better Than One: Metric+Active Learning and its Applications for IT Service Classification. 1022-1027
  
• Fei Wang, Xin Wang, Tao Li:
  Maximum Margin Clustering on Data Manifolds. 1028-1033
  
• Xiang Wang, Ian Davidson:
  Discovering Contexts and Contextual Outliers Using Random Walks in Graphs. 1034-1039
  
• Yang Wang, Mingyuan An:
  Effective Criterion Functions for Efficient Agglomerative Clustering on Very Large Networks. 1040-1045
  
• Jinlong Wu:
  Binomial Matrix Factorization for Discrete Collaborative Filtering. 1046-1051
  
• Jing Xia, Doina Caragea, William H. Hsu:
  Bi-relational Network Analysis Using a Fast Random Walk with Restart. 1052-1057
  
• Tengke Xiong, Shengrui Wang, André Mayers, Ernest Monga:
  A New MCA-Based Divisive Hierarchical Algorithm for Clustering Categorical Data. 1058-1063
  
• Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muhammad Atif Tahir:
  Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis. 1064-1069
  
• Jia Zeng, William K. Cheung, Chun-hung Li, Jiming Liu:
  Multirelational Topic Models. 1070-1075
  
• Yifeng Zeng, Yanping Xiang, Jorge Cordero Hernandez, Yujian Lin:
  Learning Local Components to Understand Large Bayesian Networks. 1076-1081
  
• Shijie Zhang, Jiong Yang, Shirong Li:
  RING: An Integrated Method for Frequent Representative Subgraph Mining. 1082-1087
  
• Gang Zhao, Yun Xiong, Longbing Cao, Dan Luo, Xuchun Su, Yangyong Zhu:
  A Cost-Effective LSH Filter for Fast Pairwise Mining. 1088-1093
  
• Xiaofei Zhou, Wenhan Jiang, Yingjie Tian, Peng Zhang, Guangli Nie, Yong Shi:
  A New Kernel-Based Classification Algorithm. 1094-1099