Principles of Data Mining and Knowledge Discovery

Third European Conference, PKDD’99, Prague, Czech Republic, September 15-18, 1999. Proceedings

  • Jan M. Żytkow
  • Jan Rauch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1704)

Table of contents

  1. Front Matter
  2. Session 1A - Time Series

    1. Eamonn J. Keogh, Michael J. Pazzani
      Pages 1-11
    2. Zbigniew R. Struzik, Arno Siebes
      Pages 12-22
  3. Session 1B - Applications

    1. Hendrik Blockeel, Sašo Džeroski, Jasna Grbović
      Pages 32-40
    2. Elisa Bertino, Barbara Catania, Eleonora Caglio
      Pages 41-50
  4. Session 2A - Taxonomies and Partitions

    1. Gou Masuda, Rei Yano, Norihiro Sakamoto, Kazuo Ushijima
      Pages 61-70
    2. F. A. El-Mouadib, J. Koronacki, J. M. Żytkow
      Pages 71-79
    3. Tapio Elomaa, Juho Rousu
      Pages 89-97
  5. Session 2B - Logic Methods

    1. Ljupčo Todorovski, Sašo Džeroski
      Pages 98-106
    2. Andrzej Skowron, Hung Son Nguyen
      Pages 107-115
    3. Fosca Giannotti, Giuseppe Manco
      Pages 125-135
  6. Session 3A - Distributed and Multirelational Databases

    1. Ning Zhong, Y. Y. Yao, Setsuo Ohsuga
      Pages 136-146
    2. Rónán Páircéir, Sally McClean, Bryan Scotney
      Pages 156-164
  7. Session 3B - Text Mining and Feature Selection

    1. Ronen Feldman, Yonatan Aumann, Moshe Fresko, Orly Liphstat, Binyamin Rosenfeld, Yonatan Schler
      Pages 165-173
    2. Chris Clifton, Robert Cooley
      Pages 174-183

About these proceedings

Introduction

This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999.
The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

Keywords

Data Mining Information Extraction Intelligent Data Analysis Text Mining database knowledge knowledge discovery logic

Editors and affiliations

  • Jan M. Żytkow
    • 1
  • Jan Rauch
    • 2
  1. 1.Computer Science DepartmentUNC Charlotte, Charlotte, N.C. 28223 and Institute of Computer Science, Polish Academy of Sciences 
  2. 2.Faculty of Informatics and StatisticsUniversity of Economics, PraguePragueCzech Republic

Bibliographic information

  • DOI https://doi.org/10.1007/b72280
  • Copyright Information Springer-Verlag Berlin Heidelberg 1999
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-66490-1
  • Online ISBN 978-3-540-48247-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349