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Principles of Data Mining and Knowledge Discovery

First European Symposium, PKDD '97, Trondheim, Norway, June 24-27, 1997 Proceedings

  • Conference proceedings
  • © 1997

Overview

Editors:
  1. Jan Komorowski
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  2. Jan Zytkow
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1263)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: PKDD 1997.

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Table of contents (43 papers)

  1. Front Matter

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  2. Knowledge discovery — A control theory perspective

    • Bjarne A. Foss
    Pages 1-3

  3. Modelling customer retention with Rough Data Models

    • Wojciech Kowalczyk, Frank Slisser
    Pages 4-13

  4. Share based measures for itemsets

    • Colin L. Carter, Howard J. Hamilton, Nick Cercone
    Pages 14-24

  5. Parallel knowledge discovery using domain generalization graphs

    • Robert J. Hilderman, Howard J. Hamilton, Robert J. Kowalchuk, Nick Cercone
    Pages 25-35

  6. Rough set theory and rule induction techniques for discovery of attribute dependencies in medical information systems

    • Jerzy Stefanowski, Krzysztof SlowiÅ„ski
    Pages 36-46

  7. Logical calculi for knowledge discovery in databases

    • Jan Rauch
    Pages 47-57

  8. Extraction of experts' decision process from clinical databases using rough set model

    • Shusaku Tsumoto
    Pages 58-67

  9. Discovering of health risks and case-based forecasting of epidemics in a health surveillance system

    • M. Bull, G. Kundt, L. Gierl
    Pages 68-77

  10. An algorithm for multi-relational discovery of subgroups

    • Stefan Wrobel
    Pages 78-87

  11. Finding similar time series

    • Gautam Das, Dimitrios Gunopulos, Heikki Mannila
    Pages 88-100

  12. Exploration of document collections with self-organizing maps: A novel approach to similarity representation

    • Dieter Merkl
    Pages 101-111

  13. Pattern based browsing in document collections

    • Ronen Feldman, Willi Klösgen, Yaniv Ben-Yehuda, Gil Kedar, Vladimir Reznikov
    Pages 112-122

  14. Induction of fuzzy characteristic rules

    • Dan Rasmussen, Ronald R. Yager
    Pages 123-133

  15. Regression-based classification methods and their comparison with decision tree algorithms

    • Mikhail V. Kiselev, Sergei M. Ananyan, Sergei B. Arseniev
    Pages 134-144

  16. Attribute discovery and rough sets

    • Jaroslaw Stepaniuk
    Pages 145-155

  17. Generation of rules from incomplete information systems

    • Marzena Kryszkiewicz
    Pages 156-166

  18. Knowledge discovery from software engineering data: Rough set analysis and its interaction with goal-oriented measurement

    • Günther Ruhe, Fraunhofer Gesellschaft
    Pages 167-177

  19. Efficient multisplitting on numerical data

    • Tapio Elomaa, Juho Rousu
    Pages 178-188

  20. SNOUT: An intelligent assistant for exploratory data analysis

    • P. D. Scott, A. P. M. Coxon, M. H. Hobbs, R. J. Williams
    Pages 189-199
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Keywords

About this book

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.

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