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On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming

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Knowledge Discovery Enhanced with Semantic and Social Information

Part of the book series: Studies in Computational Intelligence ((SCI,volume 220))

Abstract

In this paper we consider the problem of having ontologies as prior conceptual knowledge in Inductive Logic Programming (ILP). In particular, we take a critical look at three ILP proposals based on knowledge representation frameworks that integrate Description Logics and Horn Clausal Logic. From the comparative analysis of the three, we draw general conclusions that can be considered as guidelines for an upcoming Onto-Relational Learning aimed at extending Relational Learning to account for ontologies.

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari, Via E. Orabona 4, 70125, Bari, Italy

    Francesca A. Lisi & Floriana Esposito

Authors
  1. Francesca A. Lisi
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  2. Floriana Esposito
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Editors and Affiliations

  1. Department of Computer Science, Katholieke Universiteit Leuven, 3001, Heverlee, Belgium

    Bettina Berendt

  2. J. Stefan Institute, Jamova 39, 1000, Ljubljana, Slovenia

    Dunja Mladenič

  3. Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Via E. Orabona, 4, 70126, Bari, Italy

    Marco de Gemmis  & Giovanni Semeraro  & 

  4. ITI/FIN, Faculty of Computer Science, Otto-von-Guericke-Universitaet Magdeburg, P.O. Box 4120, D-39016, Magdeburg, Germany

    Myra Spiliopoulou

  5. Fachgebiet Wissensverarbeitung, Universität Kassel, Wilhelmshöher Allee 73, 34121, Kassel, Germany

    Gerd Stumme

  6. University of Economics, Prague, Nam.W.Churchilla 4, 13067, Praha 3, Czech Republic

    Vojtěch Svátek

  7. Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University, 16627, Prague 6, Czech Republic

    Filip Železný

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Lisi, F.A., Esposito, F. (2009). On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming. In: Berendt, B., et al. Knowledge Discovery Enhanced with Semantic and Social Information. Studies in Computational Intelligence, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01891-6_1

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  • DOI: https://doi.org/10.1007/978-3-642-01891-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01890-9

  • Online ISBN: 978-3-642-01891-6

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