Knowledge Discovery and Data Mining. Current Issues and New Applications : Current Issues and New Applications: 4th Pacific-Asia Conference, PAKDD 2000 Kyoto, Japan, April 18-20, 2000 Proceedings

The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000) was held at the Keihanna-Plaza, Kyoto, Japan, April 18 - 20, 2000. PAKDD 2000 provided an international forum for researchers and applica­ tion developers to share their original research results and practical development experiences. A wide range of current KDD topics were covered including ma­ chine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It followed the success of PAKDD 97 in Singapore, PAKDD 98 in Austraha, and PAKDD 99 in China by bringing together participants from universities, indus­ try, and government from all over the world to exchange problems and challenges and to disseminate the recently developed KDD techniques. This PAKDD 2000 proceedings volume addresses both current issues and novel approaches in regards to theory, methodology, and real world application. The technical sessions were organized according to subtopics such as Data Mining Theory, Feature Selection and Transformation, Clustering, Application of Data Mining, Association Rules, Induction, Text Mining, Web and Graph Mining. Of the 116 worldwide submissions, 33 regular papers and 16 short papers were accepted for presentation at the conference and included in this volume. Each submission was critically reviewed by two to four program committee members based on their relevance, originality, quality, and clarity. Perspective on Data Mining from Statistical Viewpoints....Pages 1-1 Inductive Databases and Knowledge Scouts....Pages 2-3 Hyperlink-Aware Mining and Analysis of the Web....Pages 4-4 Polynomial Time Matching Algorithms for Tree-Like Structured Patterns in Knowledge Discovery....Pages 5-16 Fast Discovery of Interesting Rules....Pages 17-28 Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases....Pages 29-39 Minimum Message Length Criterion for Second-Order Polynomial Model Discovery....Pages 40-48 Frequent Itemset Counting Across Multiple Tables....Pages 49-61 Frequent Closures as a Concise Representation for Binary Data Mining....Pages 62-73 An Optimization Problem in Data Cube System Design....Pages 74-85 Exception Rule Mining with a Relative Interestingness Measure....Pages 86-97 Consistency Based Feature Selection....Pages 98-109 Feature Selection for Clustering....Pages 110-121 A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases....Pages 122-133 Missing Value Estimation Based on Dynamic Attribute Selection....Pages 134-137 On Association, Similarity and Dependency of Attributes....Pages 138-141 Prototype Generation Based on Instance Filtering and Averaging....Pages 142-152 A Visual Method of Cluster Validation with Fastmap....Pages 153-164 COE: Clustering with Obstacles Entities A Preliminary Study....Pages 165-168 Combining Sampling Technique with DBSCAN Algorithm for Clustering Large Spatial Databases....Pages 169-172 Predictive Adaptive Resonance Theory and Knowledge Discovery in Databases....Pages 173-176 Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging....Pages 177-180 Attribute Transformations on Numerical Databases....Pages 181-192 Efficient Detection of Local Interactions in the Cascade Model....Pages 193-203 Extracting Predictors of Corporate Bankruptcy: Empirical Study on Data Mining Methods....Pages 204-207 Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets....Pages 208-211 Discovering Protein Functional Models Using Inductive Logic Programming....Pages 212-215 Mining Web Transaction Patterns in an Electronic Commerce Environment....Pages 216-219 Making Use of the Most Expressive Jumping Emerging Patterns for Classification....Pages 220-232 Mining Structured Association Patterns from Databases....Pages 233-244 Association Rules....Pages 245-256 Density-Based Mining of Quantitative Association Rules....Pages 257-268 AViz: A Visualization System for Discovering Numeric Association Rules....Pages 269-280 Discovering Unordered and Ordered Phrase Association Patterns for Text Mining....Pages 281-293 Using Random Walks for Mining Web Document Associations....Pages 294-305 A Concurrent Approach to the Key-Preserving Attribute-Oriented Induction Method....Pages 306-316 Scaling Up a Boosting-Based Learner via Adaptive Sampling....Pages 317-328 Adaptive Boosting for Spatial Functions with Unstable Driving Attributes....Pages 329-340 Robust Ensemble Learning for Data Mining....Pages 341-344 Interactive Visualization in Mining Large Decision Trees....Pages 345-348 VQTree: Vector Quantization for Decision Tree Induction....Pages 349-359 Making Knowledge Extraction and Reasoning Closer....Pages 360-371 Discovery of Relevant Weights by Minimizing Cross-Validation Error....Pages 372-375 Efficient and Comprehensible Local Regression....Pages 376-379 Information Granules for Spatial Reasoning....Pages 380-383 Uncovering the Hierarchical Structure of Text Archives by Using an Unsupervised Neural Network with Adaptive Architecture....Pages 384-395 Mining Access Patterns Efficiently from Web Logs....Pages 396-407 A Comparative Study of Classification Based Personal E-mail Filtering....Pages 408-419 Extension of Graph-Based Induction for General Graph Structured Data....Pages 420-431 Text-Source Discovery and GlOSS Update in a Dynamic Web....Pages 432-441 Extraction of Fuzzy Clusters from Weighted Graphs....Pages 442-453 Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms....Pages 454-457

This book constitutes the refereed proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000, held in Kyoto, Japan, in April 2000.
The 33 revised full papers and 16 short papers presented were carefully reviewed and selected from a total of 116 submissions. The papers are organized in sections on data mining theory; feature selection and transformation; clustering; applications of data mining; association rules and related topics; induction; text, web, and graph mining.