Principles of Data Mining and Knowledge Discovery: 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001 Proceedings / Edition 1

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Overview

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.

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Table of Contents

Self Similar Layered Hidden Markov Models 1
Automatic Text Summarization Using Unsupervised and Semi-supervised Learning 16
Detecting Temporal Changes in Event Sequences: An Application to Demographic Data 29
Knowledge Discovery in Multi-label Phenotype Data 42
Computing Association Rules Using Partial Totals 54
Gaphyl: A Genetic Algorithms Approach to Cladistics 67
Parametric Approximation Algorithms for High-Dimensional Euclidean Similarity 79
Data Structures for Minimization of Total Within-Group Distance for Spatio-Temporal Clustering 91
Non-crisp Clustering by Fast, Convergent, and Robust Algorithms 103
Pattern Extraction for Time Series Classification 115
Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study 128
Interesting Fuzzy Association Rules in Quantitative Databases 140
Interestingness Measures for Fuzzy Association Rules 152
A Data Set Oriented Approach for Clustering Algorithm Selection 165
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection 180
Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series 192
Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB 204
Using Grammatical Inference to Automate Information Extraction from the Web 216
Biological Sequence Data Mining 228
Implication-Based Fuzzy Association Rules 241
A General Measure of Rule Interestingness 253
Error Correcting Codes with Optimized Kullback-Leibler Distances for Text Categorization 266
Propositionalisation and Aggregates 277
Algorithms for the Construction of Concept Lattices and Their Diagram Graphs 289
Data Reduction Using Multiple Models Integration 301
Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution 314
Sentence Filtering for Information Extraction in Genomics, a Classification Problem 326
Text Categorization and Semantic Browsing with Self-Organizing Maps on Non-euclidean Spaces 338
A Study on the Hierarchical Data Clustering Algorithm Based on Gravity Theory 350
Internet Document Filtering Using Fourier Domain Scoring 362
Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation 374
Automatic Construction and Refinement of a Class Hierarchy over Multi-valued Data 386
Comparison of Three Objective Functions for Conceptual Clustering 399
Identification of ECG Arrhythmias Using Phase Space Reconstruction 411
Finding Association Rules That Trade Support Optimally against Confidence 424
Bloomy Decision Tree for Multi-objective Classification 436
Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction 448
Mining Positive and Negative Knowledge in Clinical Databases Based on Rough Set Model 460
The TwoKey Plot for Multiple Association Rules Control 472
Lightweight Collaborative Filtering Method for Binary-Encoded Data 484
Support Vectors for Reinforcement Learning 492
Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining 493
Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining 494
The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery 495
Scallability, Search, and Sampling: From Smart Algorithms to Active Discovery 507
Author Index 509
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