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Discovery Science

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

  • Conference proceedings
  • © 2008

Overview

Editors:
  1. Jean-François Jean-Fran

    1. INSA Lyon, LIRIS CNRS UMR 5205, University of Lyon, Villeurbanne Cedex, France

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  2. Michael R. Berthold

    1. Department of Computer and Information Science, University of Konstanz, Konstanz, Germany

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  3. Tamás Horváth

    1. University of Bonn and Fraunhofer IAIS, Sankt Augustin, Germany

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

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

Included in the following conference series:

Conference proceedings info: DS 2008.

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About this book

It is our pleasure to present the proceedings of Discovery Science 2008, the 11th International Conference on Discovery Science held in Budapest, Hungary, October 13-16, 2008. It was co-located with ALT 2008, the 19th International Conference on Algorithmic Learning Theory, whose proceedings are available in the twin volume LNAI 5254. This combination of DS and ALT conferences has been successfully organized each year since 2002. It provides a forum for the researchersworking on many di?erent aspects of scienti?c discovery. Indeed, ALT/DS 2008 covered both the possibility to automate part of the scienti?c discoveryandthenecessarysupporttothehumanprocessofdiscoveryinscience. Interestingly, this co-location also provided the opportunity for an exciting joint program of tutorials and invited talks. The number of submitted papers was 58, i.e., slightly more than the previous year. The Program Committee members were involved in a rigorous selection process based on three reviews per paper. At the end, we selected 26 long papers thanks to the recommendations of the experts based on relevance, novelty, signi?cance, technical quality, and clarity. Although some short papers were submitted, none of them was selected.

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Keywords

Table of contents (31 papers)

  1. Front Matter

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  3. Learning

    1. Unsupervised Classifier Selection Based on Two-Sample Test

      • Timo Aho, Tapio Elomaa, Jussi Kujala
      Pages 28-39

    2. An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics

      • Frederik Janssen, Johannes Fürnkranz
      Pages 40-51

    3. Learning Model Trees from Data Streams

      • Elena Ikonomovska, Joao Gama
      Pages 52-63

    4. Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees

      • Beau Piccart, Jan Struyf, Hendrik Blockeel
      Pages 64-75

    5. Ensemble-Trees: Leveraging Ensemble Power Inside Decision Trees

      • Albrecht Zimmermann
      Pages 76-87

    6. A Comparison between Neural Network Methods for Learning Aggregate Functions

      • Werner Uwents, Hendrik Blockeel
      Pages 88-99

  4. Feature Selection

    1. Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns

      • Mikko Korpela, Harri Mäkinen, Mika Sulkava, Pekka Nöjd, Jaakko Hollmén
      Pages 100-111

    2. Feature Selection in Taxonomies with Applications to Paleontology

      • Gemma C. Garriga, Antti Ukkonen, Heikki Mannila
      Pages 112-123

  5. Associations

    1. Deduction Schemes for Association Rules

      • José L. Balcázar
      Pages 124-135

    2. Constructing Iceberg Lattices from Frequent Closures Using Generators

      • Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin
      Pages 136-147

  6. Discovery Processes

    1. Learning from Each Other

      • Christopher Dartnell, Éric Martin, Jean Sallantin
      Pages 148-159

    2. Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces

      • Wolfgang Kienreich, Peter Kraker
      Pages 160-171

    3. A Framework for Knowledge Discovery in a Society of Agents

      • Gauvain Bourgne, Vincent Corruble
      Pages 172-184

  7. Learning and Chemistry

    1. Active Learning for High Throughput Screening

      • Kurt De Grave, Jan Ramon, Luc De Raedt
      Pages 185-196
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Other volumes

  1. Discovery Science

Editors and Affiliations

  • INSA Lyon, LIRIS CNRS UMR 5205, University of Lyon, Villeurbanne Cedex, France

    Jean-François Jean-Fran

  • Department of Computer and Information Science, University of Konstanz, Konstanz, Germany

    Michael R. Berthold

  • University of Bonn and Fraunhofer IAIS, Sankt Augustin, Germany

    Tamás Horváth

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