数据开采与知识发现原理/会议录Principles of data mining and knowledge discovery(数据开采与知识发现原理/会议录)

作者: Tapio Elomaa 著

出版社: 湖南文艺出版社

出版时间: 2002-12

版次: 1

ISBN: 9783540440376

定价: 678.00

装帧: 平装

开本: 其他

纸张: 胶版纸

页数: 514页

分类: 计算机与互联网

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. 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
内容简介:
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.
目录:
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