9. SDM 2009: Sparks, Nevada, USA

• Preface, Message from the Conference Co-Chair Acknowledgments.
  

Session S1: Clustering

• Xin Jin, Sangkyum Kim, Jiawei Han, Liangliang Cao, Zhijun Yin:
  GAD: General Activity Detection for Fast Clustering on Large Data. 2-13
  
• Andrej Taliun, Michael H. Böhlen, Arturas Mazeika:
  CORE: Nonparametric Clustering of Large Numeric Databases. 14-25
  
• Élisa Fromont, Adriana Prado, Céline Robardet:
  Constraint-Based Subspace Clustering. 26-37
  
• Fei Wang, Chris H. Q. Ding, Tao Li:
  Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations. 38-48
  
• Xinhai Liu, Shi Yu, Yves Moreau, Bart De Moor, Wolfgang Glänzel, Frizo A. L. Janssens:
  Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets. 49-60
  

Session S2: Time Series

• Dan Preston, Pavlos Protopapas, Carla E. Brodley:
  Event Discovery in Time Series. 61-72
  
• Nishant A. Mehta, Alexander G. Gray:
  FuncICA for Time Series Pattern Discovery. 73-84
  
• Lexiang Ye, Xiaoyue Wang, Eamonn J. Keogh, Agenor Mafra-Neto:
  Autocannibalistic and Anyspace Indexing Algorithms with Application to Sensor Data Mining. 85-96
  
• Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe, Yan Liu:
  Proximity-Based Anomaly Detection Using Sparse Structure Learning. 97-108
  
• Michail Vlachos, Suleyman Serdar Kozat, Philip S. Yu:
  Optimal Distance Bounds on Time-Series Data. 109-120
  

Session S3: Statistical Methods and Applications

• Markus Müller, Christoph Schlieder, Axel Blumenstock:
  Application of Bayesian Partition Models in Warranty Data Analysis. 121-132
  
• Martin Renqiang Min, Rui Kuang, Anthony J. Bonner, Zhaolei Zhang:
  Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery. 133-144
  
• Xingwei Yang, Longin Jan Latecki, Dragoljub Pokrajac:
  Outlier Detection with Globally Optimal Exemplar-Based GMM. 145-154
  
• Jingrui He, Jaime G. Carbonell:
  Prior-Free Rare Category Detection. 155-163
  
• Jianqiang Shen, Thomas G. Dietterich:
  A Family of Large Margin Linear Classifiers and Its Application in Dynamic Environments. 164-172
  

Session S4: Unsupervised Learning and Clustering

• Emmanuel Müller, Ira Assent, Ralph Krieger, Stephan Günnemann, Thomas Seidl:
  DensEst: Density Estimation for Data Mining in High Dimensional Spaces. 173-184
  
• Varun Chandola, Shyam Boriah, Vipin Kumar:
  A Framework for Exploring Categorical Data. 185-196
  
• Faris Alqadah, Raj Bhatnagar:
  Discovering Substantial Distinctions among Incremental Bi-Clusters. 197-208
  
• Hongjun Wang, Hanhuai Shan, Arindam Banerjee:
  Bayesian Cluster Ensembles. 209-220
  
• Xiaotong Yuan, Bao-Gang Hu, Ran He:
  Agglomerative Mean-Shift Clustering via Query Set Compression. 221-232
  

Session S5: Data Stream Mining

• Anton Dries, Ulrich Rückert:
  Adaptive Concept Drift Detection. 233-244
  
• Kamalika Das, Kanishka Bhaduri, Sugandha Arora, Wesley Griffin, Kirk D. Borne, Chris Giannella, Hillol Kargupta:
  Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms. 245-156
  
• Xiaoli Li, Philip S. Yu, Bing Liu, See-Kiong Ng:
  Positive Unlabeled Learning for Data Stream Classification. 257-268
  
• Graham Cormode, Srikanta Tirthapura, Bojian Xu:
  Time-Decayed Correlated Aggregates over Data Streams. 269-280
  
• Oksana Yakhnenko, Vasant Honavar:
  Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence. 281-294
  

Poster Spotlights

• Silvia Chiappa, Hiroto Saigo, Koji Tsuda:
  A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection. 295-304
  
• Alexandre Plastino, Erick R. Fonseca, Richard Fuchshuber, Simone L. Martins, Alex Alves Freitas, Martino Luis, Saïd Salhi:
  A Hybrid Data Mining Metaheuristic for the p-Median Problem. 305-316
  
• Boris Cule, Bart Goethals, Céline Robardet:
  A New Constraint for Mining Sets in Sequences. 317-328
  
• Frederik Janssen, Johannes Fürnkranz:
  A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. 329-340
  
• Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
  A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. 341-352
  
• Brian Quanz, Jun Huan:
  Aligned Graph Classification with Regularized Logistic Regression. 353-364
  
• Michael L. Wick, Aron Culotta, Khashayar Rohanimanesh, Andrew McCallum:
  An Entity Based Model for Coreference Resolution. 365-376
  
• Sampath Kameshwaran, Sameep Mehta, Vinayaka Pandit, Gyana R. Parija, Sudhanshu Singh, Nukala Viswanadham:
  Analyses for Service Interaction Networks with Applications to Service Delivery. 377-388
  
• Yoshinobu Kawahara, Masashi Sugiyama:
  Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation. 389-400
  
• R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst:
  Context Aware Trace Clustering: Towards Improving Process Mining Results. 401-412
  
• Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster:
  Detection and Characterization of Anomalies in Multivariate Time Series. 413-424
  
• Wei Ding, Tomasz F. Stepinski, Josue Salazar:
  Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets. 425-436
  
• Francesco Gullo, Andrea Tagarelli, Sergio Greco:
  Diversity-Based Weighting Schemes for Clustering Ensembles. 437-448
  
• Jie Chen, Yousef Saad:
  Divide and Conquer Strategies for Effective Information Retrieval. 449-460
  
• K. Zhai, W. K. Ng, A. R. Herianto, S. Han:
  Speeding Up Secure Computations via Embedded Caching. 461-472
  
• Abdullah Mueen, Eamonn J. Keogh, Qiang Zhu, Sydney Cash, M. Brandon Westover:
  Exact Discovery of Time Series Motifs. 473-484
  
• Gerhard Paaß, Frank Reichartz:
  Exploiting Semantic Constraints for Estimating Supersenses with CRFs. 485-496
  
• Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan, James Bailey, Kotagiri Ramamohanarao:
  Feature Weighted SVMs Using Receiver Operating Characteristics. 497-508
  
• Panagis Magdalinos, Christos Doulkeridis, Michalis Vazirgiannis:
  FEDRA: A Fast and Efficient Dimensionality Reduction Algorithm. 509-520
  
• Warren L. Davis IV, Peter Schwarz, Evimaria Terzi:
  Finding Representative Association Rules from Large Rule Collections. 521-532
  
• Hassan Sayyadi, Lise Getoor:
  FutureRank: Ranking Scientific Articles by Predicting their Future PageRank. 533-544
  
• Kun Liu, Evimaria Terzi, Tyrone Grandison:
  Highlighting Diverse Concepts in Documents. 545-556
  
• Snehal Pokharkar, Chandan K. Reddy:
  Identifying Information-Rich Subspace Trends in High-Dimensional Data. 557-568
  
• Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, Heikki Mannila:
  Low-Entropy Set Selection. 569-580
  
• Dino Pedreschi, Salvatore Ruggieri, Franco Turini:
  Measuring Discrimination in Socially-Sensitive Decision Records. 581-592
  
• Flavia Moser, Recep Colak, Arash Rafiey, Martin Ester:
  Mining Cohesive Patterns from Graphs with Feature Vectors. 593-604
  
• Florian Verhein:
  Mining Complex Spatio-Temporal Sequence Patterns. 605-616
  
• Paul Whitney, Dave Engel, Nick Cramer:
  Mining for Surprise Events Within Text Streams. 617-627
  
• Konstantin Salomatin, Yiming Yang, Abhimanyu Lad:
  Multi-field Correlated Topic Modeling. 628-637
  
• Bin Zhao, James T. Kwok, Changshui Zhang:
  Multiple Kernel Clustering. 638-649
  
• Mohammad Al Hasan, Mohammed Javeed Zaki:
  MUSK: Uniform Sampling of k Maximal Patterns. 650-661
  
• Jörn David:
  Noise Robust Classification Based on Spread Spectrum. 662-672
  
• Nikolaos Vasiloglou, Alexander G. Gray, David V. Anderson:
  Non-negative Matrix Factorization, Convexity and Isometry. 673-684
  
• Paolo D'Alberto, Ali Dasdan:
  Non-parametric Information-Theoretic Measures of One-Dimensional Distribution Functions from Continuous Time Series. 685-696
  
• Barna Saha, Lise Getoor:
  On Maximum Coverage in the Streaming Model & Application to Multi-topic Blog-Watch. 697-708
  
• Xiaowei Ying, Xintao Wu:
  On Randomness Measures for Social Networks. 709-720
  
• Charu C. Aggarwal:
  On Segment-Based Stream Modeling and Its Applications. 721-732
  
• Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka:
  On the Comparison of Relative Clustering Validity Criteria. 733-744
  
• Elad Yom-Tov, Noam Slonim:
  Parallel Pairwise Clustering. 745-755
  
• Jong Wook Kim, K. Selçuk Candan:
  PICC Counting: Who Needs Joins When You Can Propagate Efficiently?. 756-767
  
• Mummoorthy Murugesan, Chris Clifton:
  Providing Privacy through Plausibly Deniable Search. 768-779
  
• Sami Hanhijärvi, Gemma C. Garriga, Kai Puolamäki:
  Randomization Techniques for Graphs. 780-791
  
• Shuicheng Yan, Huan Wang:
  Semi-supervised Learning by Sparse Representation. 792-801
  
• Ana Paula Appel, Deepayan Chakrabarti, Christos Faloutsos, Ravi Kumar, Jure Leskovec, Andrew Tomkins:
  ShatterPlots: Fast Tools for Mining Large Graphs. 802-813
  
• Alexander Liu, Goo Jun, Joydeep Ghosh:
  Spatially Cost-Sensitive Active Learning. 814-825
  
• Christian Bird, Earl T. Barr, Andre Nash, Premkumar T. Devanbu, Vladimir Filkov, Zhendong Su:
  Structure and Dynamics of Research Collaboration in Computer Science. 826-837
  
• Daisuke Okanohara, Jun'ichi Tsujii:
  Text Categorization with All Substring Features. 838-846
  
• Xia Ning, George Karypis:
  The Set Classification Problem and Solution Methods. 847-858
  
• André Gohr, Alexander Hinneburg, Rene Schult, Myra Spiliopoulou:
  Topic Evolution in a Stream of Documents. 859-872
  
• Gaurav Tandon, Philip K. Chan:
  Tracking User Mobility to Detect Suspicious Behavior. 871-883
  

Session S6: Supervised Learning

• Abhimanyu Lad, Yiming Yang, Rayid Ghani, Bryan Kisiel:
  Toward Optimal Ordering of Prediction Tasks. 884-893
  
• Jaegul Choo, Barry L. Drake, Haesun Park:
  Hierarchical Linear Discriminant Analysis for Beamforming. 894-905
  
• Zhuang Wang, Slobodan Vucetic:
  Twin Vector Machines for Online Learning on a Budget. 906-917
  
• Adriano Veloso, Mohammed Javeed Zaki, Wagner Meira Jr., Marcos André Gonçalves:
  The Metric Dilemma: Competence-Conscious Associative Classification. 918-929
  

Session S7: Privacy and Social Networks

• Niklas Lavesson, Paul Davidsson:
  AMORI: A Metric-Based One Rule Inducer. 930-941
  
• Aris Gkoulalas-Divanis, Vassilios S. Verykios, Mohamed F. Mokbel:
  Identifying Unsafe Routes for Network-Based Trajectory Privacy. 942-953
  
• Lian Liu, Jie Wang, Jinze Liu, Jun Zhang:
  Privacy Preservation in Social Networks with Sensitive Edge Weights. 954-965
  
• Xiaowei Ying, Xintao Wu:
  Graph Generation with Prescribed Feature Constraints. 966-977
  
• Jiyang Chen, Osmar R. Zaïane, Randy Goebel:
  Detecting Communities in Social Networks Using Max-Min Modularity. 978-989
  
• Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin:
  A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks. 990-1001
  

Session S8: Relational Mining and High Performance Learning

• Mario Boley, Tamás Horváth, Stefan Wrobel:
  Efficient Discovery of Interesting Patterns Based on Strong Closedness. 1002-1013
  
• Ardian Kristanto Poernomo, Vivekanand Gopalkrishnan:
  Efficient Computation of Partial-Support for Mining Interesting Itemsets. 1014-1025
  
• Siegfried Nijssen, Luc De Raedt:
  Grammar Mining. 1026-1037
  
• Yiping Ke, James Cheng, Jeffrey Xu Yu:
  Top-k Correlative Graph Mining. 1038-1049
  
• Arifa Nisar, Waseem Ahmad, Wei-keng Liao, Alok N. Choudhary:
  High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic. 1050-1062
  

Session S9: Mining Graphs and Semi Structured Data

• Jimeng Sun, Spiros Papadimitriou, Ching-Yung Lin, Nan Cao, Shixia Liu, Weihong Qian:
  MultiVis: Content-Based Social Network Exploration through Multi-way Visual Analysis. 1063-1074
  
• Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt:
  Near-optimal Supervised Feature Selection among Frequent Subgraphs. 1075-1086
  
• Hiroki Arimura, Takeaki Uno:
  Polynomial-Delay and Polynomial-Space Algorithms for Mining Closed Sequences, Graphs, and Pictures in Accessible Set Systems. 1087-1098
  
• Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda:
  Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. 1099-1110
  
• Yi Han, Bin Zhou, Jian Pei, Yan Jia:
  Understanding Importance of Collaborations in Co-authorship Networks: A Supportiveness Analysis Approach. 1111-1122
  

Session S10: Text Mining and Data Reduction

• Duo Zhang, ChengXiang Zhai, Jiawei Han:
  Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases. 1123-1134
  
• Quanquan Gu, Jie Zhou:
  Local Relevance Weighted Maximum Margin Criterion for Text Classification. 1135-1146
  
• Jie Tang, Limin Yao, Dewei Chen:
  Multi-topic Based Query-Oriented Summarization. 1147-1158
  
• Jun Yan, Shuicheng Yan, Ning Liu, Zheng Chen:
  Straightforward Feature Selection for Scalable Latent Semantic Indexing. 1159-1170
  
• Sameer Singh, Jeremy Kubica, Scott Larsen, Daria Sorokina:
  Parallel Large Scale Feature Selection for Logistic Regression. 1171-1182
  

Session S11: Mining Spatio-Temporal Data and Efficient Learning

• Tsuyoshi Idé, Sei Kato:
  Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach. 1183-1194
  
• Seyed H. Mohammadi, Vandana Pursnani Janeja, Aryya Gangopadhyay:
  Discretized Spatio-Temporal Scan Window. 1195-1206
  
• Heikki Mannila, Evimaria Terzi:
  Finding Links and Initiators: A Graph-Reconstruction Problem. 1207-1217
  
• Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vincent D. Calhoun, Terran Lane:
  Efficient Multiplicative Updates for Support Vector Machines. 1218-1229
  
• Zheng Wang, Yangqiu Song, Changshui Zha:
  Efficient Active Learning with Boosting. 1230-1241
  

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