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© 2001

Principles of Data Mining and Knowledge Discovery

5th European Conference, PKDD 2001, Freiburg, Germany, September 3–5, 2001 Proceedings

  • Luc De Raedt
  • Arno Siebes
Conference proceedings PKDD 2001

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2168)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2168)

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Regular Papers

    1. Jafar Adibi, Wei-Min Shen
      Pages 1-15
    2. Massih-Reza Amini, Patrick Gallinari
      Pages 16-28
    3. H. Blockeel, J. Fürnkranz, A. Prskawetz, F. C. Billari
      Pages 29-41
    4. Amanda Clare, Ross D. King
      Pages 42-53
    5. Frans Coenen, Graham Goulbourne, Paul Leng
      Pages 54-66
    6. Clare Bates Congdon
      Pages 67-78
    7. Vladimir Estivill-Castro, Jianhua Yang
      Pages 103-114
    8. Fosca Giannotti, Giuseppe Manco, Franco Turini
      Pages 128-139
    9. Jeannette M. de Graaf, Walter A. Kosters, Jeroen J. W. Witteman
      Pages 140-151
    10. Attila Gyenesei, Jukka Teuhola
      Pages 152-164
    11. Maria Halkich, Michalis Vazirgiannis
      Pages 165-179
    12. Melanie Hilario, Alexandros Kalousis
      Pages 180-191
    13. Frank Höppner
      Pages 192-203
    14. Yuh-Jyh Hu
      Pages 228-240

Other volumes

  1. 12th European Conference on Machine Learning Freiburg, Germany, September 5–7, 2001 Proceedings
  2. Principles of Data Mining and Knowledge Discovery
    5th European Conference, PKDD 2001, Freiburg, Germany, September 3–5, 2001 Proceedings

About these proceedings

Introduction

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.

Keywords

algorithms data mining hidden Markov model knowledge knowledge discovery learning machine learning

Editors and affiliations

  • Luc De Raedt
    • 1
  • Arno Siebes
    • 2
  1. 1.Department of Computer ScienceAlbert-Ludwigs University FreiburgFreiburgGermany
  2. 2.Inst.of Information and Computing Sciences Dept. of Mathematics and Computer ScienceUniversity of UtrechtTB UtrechtThe Netherlands

Bibliographic information