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Principles of Data Mining and Knowledge Discovery

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Principles of Data Mining and Knowledge Discovery

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出 版 社:湖南文艺出版社

出版时间:

I S B N:3540425349

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内容简介

"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. "

作者简介



目录

Regular Paters
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 Apporoach ot Cladistics
Parametric Approximation Algorithms for High-Dimensional Euclidean Similarity
Data Structures for Minmization of Total Within-Group Distance for Spatio-Temporal Clustering
Non-crisp Clustering by Fast,Convergent,and Robust Algorithms
Pattern Extraction for Time Series Classification
Specifyling Mining Algorithms with Iterative User-Defined Aggregates:A Case Study
Interesting Fuzzy Assiciation Rules in Quantitave Databases
Interestingness Measures for Fuzzy Association Rules 15
Attila Gyenesei and Yukka Teuhola
A Data Set Oriented Approach for Clustering Algorithm Selection 16
Maria Halkidi and Miehalis Vazirgiannis
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection. 1~
Melanie Hilario and Alexandros Kalousis
Discovery of Temporal Patterns. Learning Rules about the Qualitative
Behaviour of Time Series 1!
Frank HSppner
Temporal Rule Discovery for Time-Series Satellite Images and Integration
with RDB 2
Rie Honda and Osamu Konishi
Using Grammatical Inference to Automate Information Extraction
from the Web 2
Theodore W. Hong and Keith L. Clark
Biological Sequence Data Mining 2
Yuh-Yyh Hu
Implication-Based Fuzzy Association Rules 2
Eyke Hiillermeier
A General Measure of Rule Interestingness 2
Szymon Yaroszewicz and Dan A. Simovici
Error Correcting Codes with Optimized Kullback-Leibler Distances for Text
Categorization 2
YSrg Kindermann, Gerhard Paass, and Edda Leopold
Propositionalisation and Aggregates
Arno Y. Knobbe, Marc de Haas, and Arno Siebes
Algorithms for the Construction of Concept Lattices and Their Diagram
Graphs '~
Sergei Kuznetsov and Sergei Obiedkov
Data Reduction Using Multiple Models Integration
Aleksandar O. Lazarevie and Zoran A. Obradovic
Discovering Fuzzy Classification Rules with Genetic Programming and
Co-evolution
Roberto R.F. Mendes, Fabricio de B. Voznika, Alex A. Freitas, and
.IuIio C. Nievola

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