This book constitutes the refereed proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery， PKDD 2002， held in Helsinki， Finland in August 2002.The 39 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are kernel methods， probabilistic methods， association rule mining， rough sets， sampling algorithms， pattern discovery， web text mining， meta data clustering， rule induction， information extraction， dependency detection， rare class prediction， classifier systems， text classification， temporal sequence analysis， unsupervised learning， time series analysis， medical data mining， etc.
作者簡介
暫缺《數(shù)據(jù)開采與知識發(fā)現(xiàn)原理（會議錄）》作者簡介
圖書目錄
Contributed Papers Optimized Substructure Discovery for Semi-structured Data Fast Outlier Detection in High Dimensional Spaces Data Mining in Schizophrenia Research - Preliminary Analysis Fast Algorithms for Mining Emerging Patterns On the Discovery of Weak Periodicities in Large Time Series The Need for Low Bias Algorithms in Classification Learning from Large Data Sets Mining All Non-derivable Frequent Itemsets Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance Finding Association Rules with Some Very Frequent Attributes Unsupervised Learning: Self-aggregation in Scaled Principal Component Space A Classification Approach for Prediction of Target Events in Temporal Sequences Privacy-Oriented Data Mining by Proof Checking Choose Your Words Carefully: An Empirical Study of Feature Selection Metrics for Text Generating Actionable Knowledge by Expert-Guided Subgroup Discovery Clustering Transactional Data Multiscale Comparison of Temporal Patterns in Time-Series Medical Databases Association Rules for Expressing Gradual Dependencies Support Approximations Using Bonferroni-Type Inequalities Using Condensed Representations for Interactive Association Rule Mining Predicting Rare Classes: Comparing Two-Phase Rule Induction to Cost-Sensitive Boosting Dependency Detection in MobiMine and Random Matrices Long-Term Learning for Web Search Engines Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database Involving Aggregate Functions in Multi-relational Search Information Extraction in Structured Documents Using Tree Automata Induction Algebraic Techniques for Analysis of Large Discrete-Valued Datasets Geography of Differences between Two Classes of Data …… Invited Papers Author Index
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