数据开采与知识发现原理

　　This book constitutes the refereed proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery， PKDD 2001， held in Freiburg， Germany， in September 2001.The 40 revised full papers presented together with four invited contributions were carefully reviewed and selected from close to 100 submissions. Among the topics addressed are hidden Markov models， text summarization， supervised learning， unsupervised learning， demographic data analysis， phenotype data mining， spatio-temporal clustering， Web-usage analysis， association rules， clustering algorithms， time series analysis， rule discovery， text categorization， self-organizing maps， filtering， reinforcemant learning， support vector machines， visual data mining， and machine learning.

暂缺《数据开采与知识发现原理》作者简介

Regular Papers
Self Similar Layered Hidden Markov Models
Automatic Text Summarization Using Unsupervised and Semi-supervised Learning
Detecting Temporal Changes in Event Sequences: An Application to
Demographic Data Knowledge Discovery in Multi-label Phenotype Data
Computing Association Rules Using Partial Totals
Gaphyl: A Genetic Algorithms Approach to Cladistics
Parametric Approximation Algorithms for High-Dimensional Euclidean Similarity
Data Structures for Minimization of Total Within-Group Distance for
Spatio-Temporal Clustering
Non-crisp Clustering by Fast, Convergent, and Robust Algorithms
Pattern Extraction for Time Series Classification
Specifying Mining Algorithms with Iterative User-Defined Aggregates:
A Case Study
Interesting Fuzzy Association Rules in Quantitative Databases
Interestingness Measures for Fuzzy Association Rules 1
A Data Set Oriented Approach for Clustering Algorithm Selection 1
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection. 1
Discovery of Temporal Patterns. Learning Rules about the Qualitative
Behaviour of Time Series
Temporal Rule Discovery for Time-Series Satellite Images and Integration
with RDB
Using Grammatical Inference to Automate Information Extraction
from the Web
Biological Sequence Data Mining
Implication-Based Fuzzy Association Rules
A General Measure of Rule Interestingness
Error Correcting Codes with Optimized Kullback-Leibler Distances for Text
Categorization
Propositionalisation and Aggregates
Algorithms for the Construction of Concept Lattices and Their DiagramGraphs
Sergei Kuznetsov and Sergei Obiedkov
Data Reduction Using Multiple Models Integration
Discovering Fuzzy Classification Rules with Genetic Programming and
Co-evolution
Inviter Papeis
Author Index