Principles of Data Mining and Knowledge Discovery : 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001 Proceedings / edited by Luc de Raedt, Arno Siebes.

Format:

Book

Contributor:

Raedt, Luc de, 1964- editor.

Siebes, Arno, 1958- editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 2168.

Lecture Notes in Artificial Intelligence ; 2168

Language:

English

Subjects (All):

Artificial intelligence.

Data structures (Computer science).

Database management.

Information technology.

Business--Data processing.

Business.

Information storage and retrieval.

Natural language processing (Computer science).

Artificial Intelligence.

Data Structures and Information Theory.

Database Management.

IT in Business.

Information Storage and Retrieval.

Natural Language Processing (NLP).

Local Subjects:

Artificial Intelligence.

Data Structures and Information Theory.

Database Management.

IT in Business.

Information Storage and Retrieval.

Natural Language Processing (NLP).

Physical Description:

1 online resource (DXXXII, 514 pages).

Edition:

First edition 2001.

Contained In:

Springer eBooks

Other Title:

Dedicated to Jan Zytkow

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001.

System Details:

text file PDF

Summary:

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.

Contents:

Regular Papers

Self-Similar Layered Hidden Markov Models

Automatic Text Summarization Using Unsupervised and Semi-supervised Learning

Detecting Temporal Change 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

A Data Set Oriented Approach for Clustering Algorithm Selection

Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection

Discovery of Temporal Patterns

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 Diagram Graphs

Data Reduction Using Multiple Models Integration

Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution

Sentence Filtering for Information Extraction in Genomics, a Classification Problem

Text Categorization and Semantic Browsing with Self-Organizing Maps on Non-euclidean Spaces

A Study on the Hierarchical Data Clustering Algorithm Based on Gravity Theory

Internet Document Filtering Using Fourier Domain Scoring

Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation

Automatic Construction and Refinement of a Class Hierarchy over Multi-valued Data

Comparison of Three Objective Functions for Conceptual Clustering

Identification of ECG Arrhythmias Using Phase Space Reconstruction

Finding Association Rules That Trade Support Optimally against Confidence

Bloomy Decision Tree for Multi-objective Classification

Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction

Mining Positive and Negative Knowledge in Clinical Databases Based on Rough Set Model

The TwoKey Plot for Multiple Association Rules Control

Lightweight Collaborative Filtering Method for Binary-Encoded Data

Invited Papers

Support Vectors for Reinforcement Learning

Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining

Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining

The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery

Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery.

Other Format:

Printed edition:

ISBN:

978-3-540-44794-8

9783540447948

Access Restriction:

Restricted for use by site license.