7. SDM 2007: Minneapolis, Minnesota, USA

Long Papers

• Jing Gao, Wei Fan, Jiawei Han, Philip S. Yu:
  A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions.
  
• Linyan Wang, Aijun An:
  Fast Counting with AV-Space for Efficient Rule Induction.
  
• Henrik Boström:
  Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets.
  
• J. Saketha Nath, Chiranjib Bhattacharyya:
  Maximum Margin Classifiers with Specified False Positive and False Negative Error Rates.
  
• Wei Jiang, Chris Clifton:
  AC-Framework for Privacy-Preserving Collaboration.
  
• Charu C. Aggarwal, Philip S. Yu:
  On Privacy-Preservation of Text and Sparse Binary Data with Sketches.
  
• Vitor R. Carvalho, William W. Cohen:
  Preventing Information Leaks in Email.
  
• Keke Chen, Gordon Sun, Ling Liu:
  Towards Attack-Resilient Geometric Data Perturbation.
  
• Hichem Frigui, Cheul Hwang:
  Adaptive Concept Learning through Clustering and Aggregation of Relational Data.
  
• Arun Qamra, Edward Y. Chang:
  RCMap: Efficiently Creating High-Quality Euclidean Embeddings.
  
• Ruizhang Huang, Wai Lam, Zhigang Zhang:
  Active Learning of Constraints for Semi-supervised Text Clustering.
  
• Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou:
  Mining Naturally Smooth Evolution of Clusters from Dynamic Data.
  
• Marina Meila, William Pentney:
  Clustering by weighted cuts in directed graphs.
  
• Arindam Banerjee, Sugato Basu, Srujana Merugu:
  Multi-way Clustering on Relation Graphs.
  
• Fei Wang, Changshui Zhang:
  Fast Multilevel Transduction on Graphs.
  
• Xin Yang, Sebastien Michea, Hongyuan Zha:
  Conical Dimension as an Intrinsic Dimension Estimator and its Applications.
  
• Erion Plaku, Lydia E. Kavraki:
  Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors.
  
• Charu C. Aggarwal:
  On Point Sampling Versus Space Sampling for Dimensionality Reduction.
  
• Arindam Banerjee:
  An Analysis of Logistic Models: Exponential Family Connections and Online Performance.
  
• Sandeep Pandey, Deepak Agarwal, Deepayan Chakrabarti, Vanja Josifovski:
  Bandits for Taxonomies: A Model-based Approach.
  
• Noam Goldberg, Chung-chieh Shan:
  Boosting Optimal Logical Patterns Using Noisy Data.
  
• Luc De Raedt, Albrecht Zimmermann:
  Constraint-Based Pattern Set Mining.
  
• Xiaopeng Xi, Eamonn J. Keogh, Li Wei, Agenor Mafra-Neto:
  Finding Motifs in a Database of Shapes.
  
• Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thomas S. Huang:
  Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities.
  
• Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonzalez:
  ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets.
  
• Aristides Gionis, Evimaria Terzi:
  Segmentations with Rearrangements.
  
• Jian Huang, Seyda Ertekin, Yang Song, Hongyuan Zha, C. Lee Giles:
  Efficient Multiclass Boosting Classification with Active Learning.
  
• Hamed Valizadegan, Pang-Ning Tan:
  Kernel Based Detection of Mislabeled Training Examples.
  
• Wei Fan, Ian Davidson:
  On Sample Selection Bias and Its Efficient Correction via Model Averaging and Unlabeled Examples.
  
• Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherkassky:
  Probabilistic Joint Feature Selection for Multi-task Learning.
  
• Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
  Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem.
  
• Bernard N. Sheehan, Yousef Saad:
  Higher Order Orthogonal Iteration of Tensors (HOOI) and its Relation to PCA and GLRAM.
  
• Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Faloutsos:
  Less is More: Compact Matrix Decomposition for Large Sparse Graphs.
  
• Jun Yang, Yan Liu, Eric P. Xing, Alexander G. Hauptmann:
  Harmonium Models for Semantic Video Representation and Classification.
  
• Claudia Perlich, Saharon Rosset:
  Identifying Bundles of Product Options using Mutual Information Clustering.
  
• Yang Huang, Martin Farach-Colton:
  Lattice based Clustering of Temporal Gene-Expression Matrices.
  

Short Papers

• Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
  Robust, Complete, and Efficient Correlation Clustering.
  
• Charu C. Aggarwal, Philip S. Yu:
  On Anonymization of String Data.
  
• Yijian Bai, Haixun Wang, Carlo Zaniolo:
  Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach.
  
• Arindam Banerjee, Sugato Basu:
  Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning.
  
• Michael Bertolacci, Anthony Wirth:
  Are approximation algorithms for consensus clustering worthwhile?.
  
• Albert Bifet, Ricard Gavaldà:
  Learning from Time-Changing Data with Adaptive Windowing.
  
• Yingyi Bu, Oscar Tat-Wing Leung, Ada Wai-Chee Fu, Eamonn J. Keogh, Jian Pei, Sam Meshkin:
  WAT: Finding Top-K Discords in Time Series Database.
  
• Dongwei Cao, Daniel Boley:
  A PAC Bound for Approximate Support Vector Machines.
  
• Haibin Cheng, Pang-Ning Tan, Rong Jin:
  Localized Support Vector Machine and Its Efficient Algorithm.
  
• Dejing Dou, Jun Li, Han Qin, Shiwoong Kim, Sheng Zhong:
  Understanding and Utilizing the Hierarchy of Abnormal BGP Events.
  
• Haimonti Dutta, Chris Giannella, Kirk D. Borne, Hillol Kargupta:
  Distributed Top-K Outlier Detection from Astronomy Catalogs using the DEMAC System.
  
• Hichem Frigui, Joshua Caudill:
  Mining Visual and Textual Data for Constructing a Multi-Modal Thesaurus.
  
• Khaled M. Hammouda, Mohamed S. Kamel:
  HP2PC: Scalable Hierarchically-Distributed Peer-to-Peer Clustering.
  
• Qi He, Kuiyu Chang, Ee-Peng Lim, Jun Zhang:
  Bursty Feature Representation for Clustering Text Streams.
  
• Bijit Hore, Ravi Chandra Jammalamadaka, Sharad Mehrotra:
  Flexible Anonymization For Privacy Preserving Data Publishing: A Systematic Search Based Approach.
  
• Vagelis Hristidis, Oscar Valdivia, Michail Vlachos, Philip S. Yu:
  A System for Keyword Search on Textual Streams.
  
• Tianming Hu, Hui Xiong, Sam Yuan Sung:
  Co-Preserving Patterns in Bipartite Partitioning for Topic Identification.
  
• Tsuyoshi Idé, Koji Tsuda:
  Change-Point Detection using Krylov Subspace Learning.
  
• Szymon Jaroszewicz, Marcin Korzen:
  Approximating Representations for Large Numerical Databases.
  
• Hyunsoo Kim, Haesun Park, Hongyuan Zha:
  Distance Preserving Dimension Reduction for Manifold Learning.
  
• Zhenzhen Kou, William W. Cohen:
  Stacked Graphical Models for Efficient Inference in Markov Random Fields.
  
• Hady Wirawan Lauw, Ee-Peng Lim, Ke Wang:
  Summarizing Review Scores of "Unequal" Reviewers.
  
• Daniel Lemire:
  A Better Alternative to Piecewise Linear Time Series Segmentation.
  
• Jure Leskovec, Mary McGlohon, Christos Faloutsos, Natalie S. Glance, Matthew Hurst:
  Patterns of Cascading Behavior in Large Blog Graphs.
  
• Jinze Liu, Qi Zhang, Wei Wang, Leonard McMillan, Jan Prins:
  PoClustering: Lossless Clustering of Dissimilarity Data.
  
• Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Chawla, Anastasios Viglas:
  An incremental data-stream sketch using sparse random projections.
  
• Olfa Nasraoui, Jeff Cerwinske, Carlos Rojas, Fabio A. González:
  Performance of Recommendation Systems in Dynamic Streaming Environments.
  
• Byung-Won On, Dongwon Lee:
  Scalable Name Disambiguation using Multi-level Graph Partition.
  
• Barna Saha, Pabitra Mitra:
  Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree.
  
• D. Sculley:
  Rank Aggregation for Similar Items.
  
• Bin Zhou, Jian Pei:
  Sketching Landscapes of Page Farms.
  
• György J. Simon, Vipin Kumar, Zhi-Li Zhang:
  Estimating False Negatives for Classification Problems with Cluster Structure.
  
• Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal:
  Discriminating Subsequence Discovery for Sequence Clustering.
  
• Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Wendy L. Hodges:
  Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces.
  
• Ding Yuan, W. Nick Street:
  HACS: Heuristic Algorithm for Clustering Subsets.
  
• Xiang Zhang, Wei Wang, Jun Huan:
  On Demand Phenotype Ranking through Subspace Clustering.
  
• Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen:
  Semi-Supervised Dimensionality Reduction.
  
• Chang Zhao, Jalal Mahmud, I. V. Ramakrishnan, Subramanyam Swaminathan:
  Computing Statistical Profiles of Active Sites in Proteins.
  
• Zheng Zhao, Huan Liu:
  Semi-supervised Feature Selection via Spectral Analysis.
  

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