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Proceedings of the Eighth SIAM International Conference on Data Mining

Edited by Mohammed J. Zaki, Ke Wang, Chid Apte, and Haesun Park



Proceedings in Applied Mathematics 130

Symposium held in Atlanta, GA, April 24-26, 2008.

Contents
Message from the Conference Co-Chairs; Preface; SDM 2008 Conference Organization; Program Committee; External Reviewers; Semi-Supervised Clustering via Matrix Facotization; Creating a Cluster Hierarchy under Constraints of a Partially Known Hierarchy; Constrained Co-clustering of Gene Expression Data; DATA PEELER: Constraint-Based Closed Pattern Mining in n-ary Relations; SpaRClus: Spatial Relationship Pattern-Based Hierarchial Clustering; Mining Tree Patterns with Almost Smallest Supertrees; Maximal Quasi-Bicliques with Balanced Noise Tolerance: Concepts and Co-clustering Applications; CISpan: Comprehensive Incremental Mining Algorithms of Closed Sequential Patterns for Multi-Versional Software Mining; Mining Association Rules of Simple Conjunctive Queries; Discovering Relational Item Sets Efficently; A Stagewise Lease Square Loss Function for Classification; Semi-Supervised Learning Based on Semiparametric Regularization; Roughly Balanced Bagging for Imbalanced Data; An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks; Aerosol Optical Depth Prediction from Satellite Observations by Multiple Instance Regression; Feature Selection with the logRatio Kernel; A RELIEF Based Feature Extraction Algorithm; Deterministic Latent Variable Models and Their Pitfalls; Massive-Scale Kernel Discriminant Analysis: Mining for Quasars; Dynamic Non-Parametric Mixutre Models and Recurrent Chinese Restaurant Process: With Applications to Evolutionary Clustering; Latent Variable Mining with Its Applications to Anomalous Behavior Detection; Similarity Measures for Categorical Data: A Comparative Evaluation; Gaussian Process Learning for Cyber-Attack Early Warning; Practical Private Computation and Zero-Knowledge Tools for Privacy-Perserving Distributed Data Mining; A Spamicity Approach to Web Spam Detection; Semantic Smoothing for Bayesian Text Classification with Small Training Data; Clustering from Constraint Graphs; Efficiently Mining Closed Subsequences with Gap Constraints; Semi-Supervised Classification with Universum; Finding Subgroups Having Several Descriptions: Algorithms for Redescription Mining; The PageTrust Algorithm: How to Rank Web Pages When Negative Links Are Allowed?; A Pattern Mining Approach toward Discovering Generalized Sequences Signatures; The Asymmetric Approximate Antyime Join: A New Primative with Applications to Data Mining; Preemptive Measures against Malicious Party in Privacy-Preserving Data Mining; A Range Query Approach for High Dimensional Euclidean Space Based on EDM Estimation; A Bayesian Technique for Estimating the Credibility of Question Answerers; Semi-supervised Multi-label Learning by Solving a Sylvester Equation; Exploiting Structured Reference Data for Unsupervised Text Segmentation with Conditional Random Fields; Graph Mining with Variational Dirichlet Process Mixture Models; Direct Density Ratio Estimation for Large-scale Covariate Shift Adaption; ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data; Semi-supervised Learning of a Markovian Metric; Mining Abnormal Patterns from Heterogeneous Time-Series with Irrelevant Features for Fault Event Detection; Outlier Detection with Uncertain Data; Randomization of Real-Valued Matrices for Assessing the Significance of Data Mining Results; Theoretical Analysis of Subsequences Time-Series Clustering from a Frequency-Analysis Viewpoint; Active Learning with Model Selection in Linear Regression; A Feautre Selection Algorithm Capable of Handling Extremely Large Data Dimensionality; Generic Methods for Multi-criteria Evaluation; A New Method for Rule Finding via Bootstrapped Confidence Intervals; Mining and Ranking Generators of Sequential Patterns; Type Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing; Exploration and Reduction of the Feature Space by Hierarchical Clustering; On the Dangers of Cross-Validation. An Experimental Evaluation; Mining Complex, Maximal and Complete Sub-graphs and Sets of Correlated Variables with Applications to Feature Subset Selection; Spatio-Temporal Partitioning for Improving Aerosol Prediction Accuracy; On Indexing High Dementional Data with Uncertainty; Efficient Distribution Mining Classification; Mining Sequence Classifiers for Early Prediction; Exact and Approximate Reverse Nearest Neighbor Search for Multimedia Data; Finding a Haystack in Haystacks—Simultaneous Identification of Concepts in Large Bio-Medical Corpora; Learning Markov Network Structure Using Few Independence Tests; Statistical Density Prediction in Traffic Networks; Proximity Tracking on Time-Evolving Bipartite Graphs; Integration of Multiple Networks for Robust Label Propagation; Spatial Scan Statistics for Graph Clustering; Randomizing Social Networks: A Spectrum Preserving Approach; Efficient Maximum Margin Clustering via Cutting Plane Algorithm; Robust Clustering in Arbitrarily Orient Subspaces; The Relevant-set Correlation Model for Data Clustering; Cluster Ensemble Selection; Weighted Consensus Clustering; A General Framework for Estimating Similarity of Datasets and Decision Trees: Exploring Semantic Similarity; A General Model for Multiple View Unsupervised Learning; Unsupervised Segmentation of Conversational Transcripts; Large-Scale Many-Class Learning; Simultaneous Unsupervised Learning od Disparate Clusterings; Author Index.

2008 / 869 pages + index / CD / ISBN: 978-089871-654-2
List Price $179.50 / Member Price $125.65 / Order Code PR130
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