© 2008

Discovery Science

11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008. Proceedings

  • Jean-François Jean-Fran
  • Michael R. Berthold
  • Tamás Horváth
Conference proceedings DS 2008

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5255)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5255)

Table of contents

  1. Front Matter
  2. Invited Papers

  3. Learning

    1. Timo Aho, Tapio Elomaa, Jussi Kujala
      Pages 28-39
    2. Elena Ikonomovska, Joao Gama
      Pages 52-63
    3. Beau Piccart, Jan Struyf, Hendrik Blockeel
      Pages 64-75
  4. Feature Selection

    1. Mikko Korpela, Harri Mäkinen, Mika Sulkava, Pekka Nöjd, Jaakko Hollmén
      Pages 100-111
    2. Gemma C. Garriga, Antti Ukkonen, Heikki Mannila
      Pages 112-123
  5. Associations

    1. José L. Balcázar
      Pages 124-135
    2. Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin
      Pages 136-147
  6. Discovery Processes

    1. Christopher Dartnell, Éric Martin, Jean Sallantin
      Pages 148-159
    2. Gauvain Bourgne, Vincent Corruble
      Pages 172-184
  7. Learning and Chemistry

    1. Kurt De Grave, Jan Ramon, Luc De Raedt
      Pages 185-196

About these proceedings


This book constitutes the refereed proceedings of the 11th International Conference on Discovery Science, DS 2008, held in Budapest, Hungary, in October 2008, co-located with the 19th International Conference on Algorithmic Learning Theory, ALT 2008.

The 26 revised long papers presented together with 5 invited papers were carefully reviewed and selected from 58 submissions. The papers address all current issues in the area of development and analysis of methods for intelligent data analysis, knowledge discovery and machine learning, as well as their application to scientific knowledge discovery. The papers are organized in topical sections on learning, feature selection, associations, discovery processes, learning and chemistry, clustering, structured data, and text analysis.


Clustering HCI classifier systems computational learning data analysis data mining digital encyclopedias grid computing knowledge knowledge discovery knowledge extraction knowledge processing knowledge visualization learning machine learning

Editors and affiliations

  • Jean-François Jean-Fran
    • 1
  • Michael R. Berthold
    • 2
  • Tamás Horváth
    • 3
  1. 1.INSA Lyon, LIRIS CNRS UMR 5205University of LyonVilleurbanne CedexFrance
  2. 2.Department of Computer and Information ScienceUniversity of KonstanzKonstanzGermany
  3. 3.University of Bonn and Fraunhofer IAISSankt AugustinGermany

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