This book constitutes the refereed proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining， PAKDD 2001， held in Hong Kong， China in April 2001.The 38 revised full papers and 22 short papers presented were carefully reviewed and selected from a total of 152 submissions. The book offers topical sections on Web mining， text mining， applications and tools， concept hierarchies， feature selection， interestingness， sequence mining， spatial and temporal mining， association mining， classification and rule induction， clustering， and advanced topics and new methods.
作者簡介
暫缺《知識發(fā)現(xiàn)和數(shù)據(jù)開采進(jìn)展》作者簡介
圖書目錄
Keynote Presentations Incompleteness in Data Mining Mining E-Commerce Data: The Good, the Bad, and the Ugly Seamless Integration of Data Mining with DBMS and Applications Web Mining Applying Pattern Mining to Web Information Extraction Empirical Study of Recommender Systems Using Linear Classifiers i JADE eMiner--A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (i JADE) on Internet Shopping A Characterized Rating Recommend System Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents Text Mining Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification Predictive Self-Organizing Networks for Text Categorization Meta-learning Models for Automatic Textual Document Categorization Efficient Algorithms for Concept Space Construction Topic Detection，Neural NetworksTracking, and Trend Analysis Using Self-Organizing Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps Applications and Tools Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis A Toolbox Approach to Flexible and Efficient Data Mining Determining Progression in Glaucoma Using Visual Fields Seabreeze Prediction Using Bayesian Networks Semi-supervised Learning in Medical Image Database On Application of Rough Data Mining Methods to Automatic Construction of Student Models Concept Hierarchies Concept Approximation in Concept Lattice Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data Representing Large Concept Hierarchies Using Lattice Data Structure Feature Selection Feature Selection for Temporal Health Records …… Interestingness Sequence4 Mining Spatial and Temporal Mining Association Mining Classification and Rule Induction Clustering Advanced Topics and New Methods Author Index
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