8. SDM 2008: Atlanta, Georgia, USA

• Message from the Conference Co-Chairs.
  
• Preface.
  

Constraint-Based Clustering

• Fei Wang, Tao Li, Changshui Zhang:
  Semi-Supervised Clustering via Matrix Factorization. 1-12
  
• Korinna Bade, Andreas Nürnberger:
  Creating a Cluster Hierarchy under Constraints of a Partially Known Hierarchy. 13-24
  
• Ruggero G. Pensa, Jean-François Boulicaut:
  Constrained Co-clustering of Gene Expression Data. 25-36
  
• Loïc Cerf, Jérémy Besson, Céline Robardet, Jean-François Boulicaut:
  Data Peeler: Contraint-Based Closed Pattern Mining in n-ary Relations. 37-48
  
• Sangkyum Kim, Xin Jin, Jiawei Han:
  SpaRClus: Spatial Relationship Pattern-Based Hierarchial Clustering. 49-60
  

Pattern Mining

• Jeroen De Knijf:
  Mining Tree Patterns with Almost Smallest Supertrees. 61-71
  
• Jinyan Li, Kelvin Sim, Guimei Liu, Limsoon Wong:
  Maximal Quasi-Bicliques with Balanced Noise Tolerance: Concepts and Co-clustering Applications. 72-83
  
• Ding Yuan, Kyuhyung Lee, Hong Cheng, Gopal Krishna, Zhenmin Li, Xiao Ma, Yuanyuan Zhou, Jiawei Han:
  CISpan: Comprehensive Incremental Mining Algorithms of Closed Sequential Patterns for Multi-Versional Software Mining. 84-95
  
• Bart Goethals, Wim Le Page, Heikki Mannila:
  Mining Association Rules of Simple Conjunctive Queries. 96-107
  
• Arne Koopman, Arno Siebes:
  Discovering Relational Items Sets Efficiently. 108-119
  

Classification/Regression

• Shuang-Hong Yang, Bao-Gang Hu:
  A Stagewise Least Square Loss Function for Classification. 120-131
  
• Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Christos Faloutsos:
  Semi-Supervised Learning Based on Semiparametric Regularization. 132-142
  
• Shohei Hido, Hisashi Kashima:
  Roughly Balanced Bagging for Imbalanced Data. 143-152
  
• Kanishka Bhaduri, Hillol Kargupta:
  An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks. 153-164
  
• Zhuang Wang, Vladan Radosavljevic, Bo Han, Zoran Obradovic:
  Aerosol Optical Depth Prediction from Satellite Obsercations by Multiple Instance Regression. 165-176
  

Feature Selection/Statistical Methods

• Julien Prados, Alexandros Kalousis, Melanie Hilario:
  Feature Selection with the logRatio Kernel. 177-187
  
• Yijun Sun, Dapeng Wu:
  A RELIEF Based Feature Extraction Algorithm. 188-195
  
• Max Welling, Chaitanya Chemudugunta, Nathan Sutter:
  Deterministic Latent Variable Models and Their Pitfalls. 196-207
  
• Ryan Riegel, Alexander Gray, Gordon Richards:
  Massive-Scale Kernel Discriminant Analysis: Mining for Quasars. 208-218
  
• Amr Ahmed, Eric P. Xing:
  Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering. 219-230
  

Outliers/Privacy

• Shunsuke Hirose, Kenji Yamanishi:
  Latent Variable Mining with Its Applications to Anomalous Behavior Detection. 231-242
  
• Shyam Boriah, Varun Chandola, Vipin Kumar:
  Similarity Measures for Categorical Data: A Comparative Evaluation. 243-254
  
• Jian Zhang, Phillip A. Porras, Johannes Ullrich:
  Gaussian Process Learning for Cyber-Attack Early Warning. 255-264
  
• Yitao Duan, John F. Canny:
  Practical Private Computation and Zero-Knowledge Tools for Privacy-Preserving Distributed Data Mining. 265-276
  
• Bin Zhou, Jian Pei, ZhaoHui Tang:
  A Spamicity Approach to Web Spam Detection. 277-288
  

Poster Session

• Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu:
  Semantic Smoothing for Bayesian Text Classification with Small Training Data. 289-300
  
• Ari Freund, Dan Pelleg, Yossi Richter:
  Clustering from Constraint Graphs. 301-312
  
• Chun Li, Jianyong Wang:
  Efficiently Mining Closed Subsequences with Gap Constraints. 313-322
  
• Dan Zhang, Jingdong Wang, Fei Wang, Changshui Zhang:
  Semi-Supervised Classification with Universum. 323-333
  
• Arianna Gallo, Pauli Miettinen, Heikki Mannila:
  Finding Subgroups having Several Descriptions: Algorithms for Redescription Mining. 334-345
  
• Cristobald de Kerchove, Paul Van Dooren:
  The PageTrust Algorithm: How to rank web pages when negative links are allowed? 346-352
  
• Dietmar H. Dorr, Anne Denton:
  A pattern mining approach toward discovering generalized sequence signatures. 353-362
  
• Lexiang Ye, Xiaoyue Wang, Dragomir Yankov, Eamonn J. Keogh:
  The Asymmetric Approximate Anytime Join: A New Primitive with Applications to Data Mining. 363-374
  
• Shuguo Han, Wee Keong Ng:
  Preemptive Measures against Malicious Party in Privacy-Preserving Data Mining. 375-386
  
• Kentarou Kido, Hiroshi Kuwajima, Takashi Washio:
  A Range Query Approach for High Dimensional Euclidean Space Based on EDM Estimation. 387-398
  
• Byron Dom, Deepa Paranjpe:
  A Bayesian Technique for Estimating the Credibility of question Answerers. 399-409
  
• Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang:
  Semi-supervised Multi-label Learning by Solving a Sylvester Equation. 410-419
  
• Chang Zhao, Jalal Mahmud, I. V. Ramakrishnan:
  Exploiting Structured Reference Data for Unsupervised Text Segmentation with Conditional Random Fields. 420-431
  
• Koji Tsuda, Kenichi Kurihara:
  Graph Mining with Variational Dirichlet Process Mixture Models. 432-442
  
• Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama:
  Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. 443-454
  
• M. Maruf Hossain, Md. Rafiul Hassan, James Bailey:
  ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data. 455-465
  
• Avleen Singh Bijral, Manuel E. Lladser, Gregory Z. Grudic:
  Semi-supervised Learning of a Markovian Metric. 466-471
  
• Ryohei Fujimaki, Takayuki Nakata, Hidenori Tsukahara, Akinori Sato:
  Mining Abnormal Patterns from Heterogeneous Time-Series with Irrelevant Features for Fault Event Detection. 472-482
  
• Charu C. Aggarwal, Philip S. Yu:
  Outlier Detection with Uncertain Data. 483-493
  
• Markus Ojala, Niko Vuokko, Aleksi Kallio, Niina Haiminen, Heikki Mannila:
  Randomization of real-valued matrices for assessing the significance of data mining results. 494-505
  
• Ryohei Fujimaki, Shunsuke Hirose, Takayuki Nakata:
  Theorectical Analysis of Subsequence Time-Series Clustering from a Frequency-Analysis Viewpoint. 506-517
  
• Masashi Sugiyama, Neil Rubens:
  Active Learning with Model Selection in Linear Regression. 518-529
  
• Yijun Sun, Sinisa Todorovic, Steve Goodison:
  A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality. 530-540
  
• Niklas Lavesson, Paul Davidsson:
  Generic Methods for Multi-criteria Evaluation. 541-546
  
• Norman Matloff:
  A New Method for Rule Finding Via Bootstrapped Confidence Intervals. 547-552
  
• David Lo, Siau-Cheng Khoo, Jinyan Li:
  Mining and Ranking Generators of Sequential Patterns. 553-564
  
• Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu:
  Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing. 565-576
  
• Dino Ienco, Rosa Meo:
  Exploration and Reduction of the Feature Space by Hierarchical Clustering. 577-587
  
• R. Bharat Rao, Glenn Fung:
  On the Dangers of Cross-Validation. An Experimental Evaluation. 588-596
  
• Florian Verhein:
  Mining Complex, Maximal and Complete Sub-graph and Sets of Correlated Variables with Applications to Feature Subset Selection. 597-608
  
• Vladan Radosavljevic, Slobodan Vucetic, Zoran Obradovic:
  Spatio-Temporal Partitioning for Improving Aerosol Prediction Accuracy. 609-620
  
• Charu C. Aggarwal, Philip S. Yu:
  On Indexing High Demensional Data with Uncertainty. 621-631
  
• Yasushi Sakurai, Rosalynn Chong, Lei Li, Christos Faloutsos:
  Efficient Distribution Mining and Classification. 632-643
  
• Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. Yu:
  Mining Sequence Classifiers for Early Prediction. 644-655
  
• Jessica Lin, David Etter, David DeBarr:
  Exact and Approximate Reverse Nearest Neighbor Search for Multimedia Data. 656-667
  
• Ying Liu, Lucian Vlad Lita, Radu Stefan Niculescu, Prasenjit Mitra, C. Lee Giles:
  Finding a Haystack in Haystacks - Simultaneous Identification of Concepts in Large Bio-Medical Corpora. 668-679
  
• Parichey Gandhi, Facundo Bromberg, Dimitris Margaritis:
  Learning Markov Network Structure using Few Independence Tests. 680-691
  

Graphs/Networks

• Hans-Peter Kriegel, Matthias Renz, Matthias Schubert, Andreas Züfle:
  Statistical Density Prediction in Traffic Networks. 692-703
  
• Hanghang Tong, Spiros Papadimitriou, Philip S. Yu, Christos Faloutsos:
  Proximity Tracking on Time-Evolving Bipartite Graphs. 704-715
  
• Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama:
  Integration of Multiple Networks for Robust Label Propagation. 716-726
  
• Bei Wang, Jeff M. Phillips, Robert Schreiber, Dennis M. Wilkinson:
  Spatial Scan Statistics for Graph Clustering. 727-738
  
• Xiaowei Ying, Xintao Wu:
  Randomizing Social Networks: a Spectrum Preserving Approach. 739-750
  

Clustering

• Bin Zhao, Fei Wang, Changshui Zhang:
  Efficient Maximum Margin Clustering via Cutting Plane Algorithm. 751-762
  
• Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek:
  Robust Clustering in Arbitrarily Oriented Subspaces. 763-774
  
• Michael E. Houle:
  The Relevant-set Correlation Model for Data Clustering. 775-786
  
• Xiaoli Z. Fern, Wei Lin:
  Cluster Ensemble Selection. 787-797
  
• Tao Li, Chris H. Q. Ding:
  Weighted Consensus Clustering. 798-809
  

Unsupervised Learning

• Irene Ntoutsi, Alexandros Kalousis, Yannis Theodoridis:
  A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees. 810-821
  
• Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang:
  A General Model for Multiple View Unsupervised Learning. 822-833
  
• Krishna Kummamuru, Deepak P, Shourya Roy, L. Venkata Subramaniam:
  Unsupervised Segmentation of Conversational Transcripts. 834-845
  
• Omid Madani, Michael Connor:
  Large-Scale Many-Class Learning. 846-857
  
• Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
  Simultaneous Unsupervised Learning of Disparate Clusterings. 858-869