Table of contents

  1. Front Matter
  2. Wojciech Kowalczyk, Frank Slisser
    Pages 4-13
  3. Colin L. Carter, Howard J. Hamilton, Nick Cercone
    Pages 14-24
  4. Robert J. Hilderman, Howard J. Hamilton, Robert J. Kowalchuk, Nick Cercone
    Pages 25-35
  5. Gautam Das, Dimitrios Gunopulos, Heikki Mannila
    Pages 88-100
  6. Ronen Feldman, Willi Klösgen, Yaniv Ben-Yehuda, Gil Kedar, Vladimir Reznikov
    Pages 112-122
  7. Dan Rasmussen, Ronald R. Yager
    Pages 123-133
  8. Mikhail V. Kiselev, Sergei M. Ananyan, Sergei B. Arseniev
    Pages 134-144
  9. Jaroslaw Stepaniuk
    Pages 145-155
  10. Marzena Kryszkiewicz
    Pages 156-166
  11. Tapio Elomaa, Juho Rousu
    Pages 178-188
  12. P. D. Scott, A. P. M. Coxon, M. H. Hobbs, R. J. Williams
    Pages 189-199

Other volumes

  1. 9th European Conference on Machine Learning Prague, Czech Republic, April 23–25, 1997 Proceedings
  2. Principles of Data Mining and Knowledge Discovery
    First European Symposium, PKDD '97 Trondheim, Norway, June 24–27, 1997 Proceedings

About these proceedings


This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997.
The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.


Performance artificial intelligence data mining knowledge knowledge discovery knowledge representation learning machine learning

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1997
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-63223-8
  • Online ISBN 978-3-540-69236-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book