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Inductive Logic Programming

13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003, Proceedings

  • Conference proceedings
  • © 2003

Overview

Editors:
  1. Tamás Horváth

    1. Fraunhofer IAIS, Schloss Birlinghoven, Sankt Augustin, Germany

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  2. Akihiro Yamamoto

    1. Graduate School of Informatics, Kyoto University Yoshida Honmachi, Sakyo-ku, Japan

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2835)

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

Included in the following conference series:

Conference proceedings info: ILP 2003.

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Table of contents (25 papers)

  1. Front Matter

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  2. Invited Papers

    1. A Personal View of How Best to Apply ILP

      • Ross D. King
      Pages 1-1

    2. Agents that Reason and Learn

      • John W. Lloyd
      Pages 2-3

  3. Research Papers

    1. Mining Model Trees: A Multi-relational Approach

      • Annalisa Apice, Michelangelo Ceci, Donato Malerba
      Pages 4-21

    2. Complexity Parameters for First-Order Classes

      • Marta Arias, Roni Khardon
      Pages 22-37

    3. A Multi-relational Decision Tree Learning Algorithm – Implementation and Experiments

      • Anna Atramentov, Hector Leiva, Vasant Honavar
      Pages 38-56

    4. Applying Theory Revision to the Design of Distributed Databases

      • Fernanda Baião, Marta Mattoso, Jude Shavlik, Gerson Zaverucha
      Pages 57-74

    5. Disjunctive Learning with a Soft-Clustering Method

      • Guillaume Cleuziou, Lionel Martin, Christel Vrain
      Pages 75-92

    6. ILP for Mathematical Discovery

      • Simon Colton, Stephen Muggleton
      Pages 93-111

    7. An Exhaustive Matching Procedure for the Improvement of Learning Efficiency

      • Nicola Di Mauro, Teresa Maria Altomare Basile, Stefano Ferilli, Floriana Esposito, Nicola Fanizzi
      Pages 112-129

    8. Efficient Data Structures for Inductive Logic Programming

      • Nuno Fonseca, Ricardo Rocha, Rui Camacho, Fernando Silva
      Pages 130-145

    9. Graph Kernels and Gaussian Processes for Relational Reinforcement Learning

      • Thomas Gärtner, Kurt Driessens, Jan Ramon
      Pages 146-163

    10. On Condensation of a Clause

      • Kouichi Hirata
      Pages 164-179

    11. A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting

      • Susanne Hoche, Stefan Wrobel
      Pages 180-196

    12. Comparative Evaluation of Approaches to Propositionalization

      • Mark-A. Krogel, Simon Rawles, Filip Železný, Peter A. Flach, Nada Lavrač, Stefan Wrobel
      Pages 197-214

    13. Ideal Refinement of Descriptions in \(\mathcal{AL}\)-Log

      • Francesca A. Lisi, Donato Malerba
      Pages 215-232

    14. Which First-Order Logic Clauses Can Be Learned Using Genetic Algorithms?

      • Flaviu Adrian Mărginean
      Pages 233-250

    15. Improved Distances for Structured Data

      • Dimitrios Mavroeidis, Peter A. Flach
      Pages 251-268

    16. Induction of Enzyme Classes from Biological Databases

      • Stephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe
      Pages 269-280

    17. Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars

      • Tim Oates, Shailesh Doshi, Fang Huang
      Pages 281-298
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  1. Inductive Logic Programming

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Editors and Affiliations

  • Fraunhofer IAIS, Schloss Birlinghoven, Sankt Augustin, Germany

    Tamás Horváth

  • Graduate School of Informatics, Kyoto University Yoshida Honmachi, Sakyo-ku, Japan

    Akihiro Yamamoto

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