Advances in Knowledge Discovery and Data Mining : 10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings

Keynote Speech.- Protection or Privacy? Data Mining and Personal Data.- The Changing Face of Web Search.- Invited Speech.- Data Mining for Surveillance Applications.- Classification.- A Multiclass Classification Method Based on Output Design.- Regularized Semi-supervised Classification on Manifold.- Similarity-Based Sparse Feature Extraction Using Local Manifold Learning.- Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees.- RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification.- TRIPPER: Rule Learning Using Taxonomies.- Using Weighted Nearest Neighbor to Benefit from Unlabeled Data.- Constructive Meta-level Feature Selection Method Based on Method Repositories.- Ensemble Learning.- Variable Randomness in Decision Tree Ensembles.- Further Improving Emerging Pattern Based Classifiers Via Bagging.- Improving on Bagging with Input Smearing.- Boosting Prediction Accuracy on Imbalanced Datasets with SVM Ensembles.- Ensemble Learning.- DeLi-Clu: Boosting Robustness, Completeness, Usability, and Efficiency of Hierarchical Clustering by a Closest Pair Ranking.- Iterative Clustering Analysis for Grouping Missing Data in Gene Expression Profiles.- An EM-Approach for Clustering Multi-Instance Objects.- Mining Maximal Correlated Member Clusters in High Dimensional Database.- Hierarchical Clustering Based on Mathematical Optimization.- Clustering Multi-represented Objects Using Combination Trees.- Parallel Density-Based Clustering of Complex Objects.- Neighborhood Density Method for Selecting Initial Cluster Centers in K-Means Clustering.- Uncertain Data Mining: An Example in Clustering Location Data.- Support Vector Machines.- Parallel Randomized Support Vector Machine.- ?-Tube Based Pattern Selection for Support Vector Machines.- Self-adaptive Two-Phase Support Vector Clustering for Multi-Relational Data Mining.- One-Class Support Vector Machines for Recommendation Tasks.- Text and Document Mining.- Heterogeneous Information Integration in Hierarchical Text Classification.- FISA: Feature-Based Instance Selection for Imbalanced Text Classification.- Dynamic Category Profiling for Text Filtering and Classification.- Detecting Citation Types Using Finite-State Machines.- A Systematic Study of Parameter Correlations in Large Scale Duplicate Document Detection.- Comparison of Documents Classification Techniques to Classify Medical Reports.- XCLS: A Fast and Effective Clustering Algorithm for Heterogenous XML Documents.- Clustering Large Collection of Biomedical Literature Based on Ontology-Enriched Bipartite Graph Representation and Mutual Refinement Strategy.- Web Mining.- Level-Biased Statistics in the Hierarchical Structure of the Web.- Cleopatra: Evolutionary Pattern-Based Clustering of Web Usage Data.- Extracting and Summarizing Hot Item Features Across Different Auction Web Sites.- Clustering Web Sessions by Levels of Page Similarity.- i Wed: An Integrated Multigraph Cut-Based Approach for Detecting Events from a Website.- Enhancing Duplicate Collection Detection Through Replica Boundary Discovery.- Graph and Network Mining.- Summarization and Visualization of Communication Patterns in a Large-Scale Social Network.- Patterns of Influence in a Recommendation Network.- Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction.- Combining Smooth Graphs with Semi-supervised Classification.- Network Data Mining: Discovering Patterns of Interaction Between Attributes.- Association Rule Mining.- SGPM: Static Group Pattern Mining Using Apriori-Like Sliding Window.- Mining Temporal Indirect Associations.- Mining Top-K Frequent Closed Itemsets Is Not in APX.- Quality-Aware Association Rule Mining.- IMB3-Miner: Mining Induced/Embedded Subtrees by Constraining the Level of Embedding.- Maintaining Frequent Itemsets over High-Speed Data Streams.- Generalized Disjunction-Free Representation of Frequents Patterns with at Most k Negations.- Mining Interesting Imperfectly Sporadic Rules.- Improved Negative-Border Online Mining Approaches.- Association-Based Dissimilarity Measures for Categorical Data: Limitation and Improvement.- Is Frequency Enough for Decision Makers to Make Decisions?.- Ramp: High Performance Frequent Itemset Mining with Efficient Bit-Vector Projection Technique.- Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices.- Bio-data Mining.- Scoring Method for Tumor Prediction from Microarray Data Using an Evolutionary Fuzzy Classifier.- Efficient Discovery of Structural Motifs from Protein Sequences with Combination of Flexible Intra- and Inter-block Gap Constraints.- Finding Consensus Patterns in Very Scarce Biosequence Samples from Their Minimal Multiple Generalizations.- Kernels on Lists and Sets over Relational Algebra: An Application to Classification of Protein Fingerprints.- Mining Quantitative Maximal Hyperclique Patterns: A Summary of Results.- Outlier and Intrusion Detection.- A Nonparametric Outlier Detection for Effectively Discovering Top-N Outliers from Engineering Data.- A Fast Greedy Algorithm for Outlier Mining.- Ranking Outliers Using Symmetric Neighborhood Relationship.- Construction of Finite Automata for Intrusion Detection from System Call Sequences by Genetic Algorithms.- An Adaptive Intrusion Detection Algorithm Based on Clustering and Kernel-Method.- Weighted Intra-transactional Rule Mining for Database Intrusion Detection.- Privacy.- On Robust and Effective K-Anonymity in Large Databases.- Achieving Private Recommendations Using Randomized Response Techniques.- Privacy-Preserving SVM Classification on Vertically Partitioned Data.- Relational Database.- Data Mining Using Relational Database Management Systems.- Bias-Free Hypothesis Evaluation in Multirelational Domains.- Enhanced DB-Subdue: Supporting Subtle Aspects of Graph Mining Using a Relational Approach.- Multimedia Mining.- Multimedia Semantics Integration Using Linguistic Model.- A Novel Indexing Approach for Efficient and Fast Similarity Search of Captured Motions.- Mining Frequent Spatial Patterns in Image Databases.- Image Classification Via LZ78 Based String Kernel: A Comparative Study.- Stream Data Mining.- Distributed Pattern Discovery in Multiple Streams.- COMET: Event-Driven Clustering over Multiple Evolving Streams.- Variable Support Mining of Frequent Itemsets over Data Streams Using Synopsis Vectors.- Hardware Enhanced Mining for Association Rules.- A Single Index Approach for Time-Series Subsequence Matching That Supports Moving Average Transform of Arbitrary Order.- Efficient Mining of Emerging Events in a Dynamic Spatiotemporal Environment.- Temporal Data Mining.- A Multi-Hierarchical Representation for Similarity Measurement of Time Series.- Multistep-Ahead Time Series Prediction.- Sequential Pattern Mining with Time Intervals.- A Wavelet Analysis Based Data Processing for Time Series of Data Mining Predicting.- Temporal Data Mining.- Intelligent Particle Swarm Optimization in Multi-objective Problems.- Hidden Space Principal Component Analysis.- Neighbor Line-Based Locally Linear Embedding.- Predicting Rare Extreme Values.- Domain-Driven Actionable Knowledge Discovery in the Real World.- Evaluation of Attribute-Aware Recommender System Algorithms on Data with Varying Characteristics.- Innovative Applications.- An Intelligent System Based on Kernel Methods for Crop Yield Prediction.- A Machine Learning Application for Human Resource Data Mining Problem.- Towards Automated Design of Large-Scale Circuits by Combining Evolutionary Design with Data Mining.- Mining Unexpected Associations for Signalling Potential Adverse Drug Reactions from Administrative Health Databases.