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Efficient Evaluation of Candidate Hypotheses in \(\mathcal{AL}\)-log

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Inductive Logic Programming (ILP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3194))

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Abstract

In this paper we face the coverage problem in the context of learning in the hybrid language \(\mathcal{AL}\)-log. Here candidate hypotheses are represented as Datalog clauses with variables constrained by assertions in the description logic \(\mathcal{ALC}\). Regardless of the scope of induction we define coverage relations for \(\mathcal{AL}\)-log in the two logical settings of learning from implications and learning from interpretations. Also, with reference to the ILP system \(\mathcal{AL}\)-QuIn, we discuss our solutions to the algorithmic and implementation issues raised by the coverage test for the setting of characteristic induction from interpretations in \(\mathcal{AL}\)-log.

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, University of Bari, Italy

    Francesca A. Lisi & Floriana Esposito

Authors
  1. Francesca A. Lisi
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  2. Floriana Esposito
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Editor information

Editors and Affiliations

  1. Faculdade de Engenharia & LIAAD, Universidade do Porto, Portugal

    Rui Camacho

  2. Department of Computer Science, Penglais, Aberystwyth, Ceredigion, University of Wales, SY23 3DB, Wales, UK

    Ross King

  3. Dept. of Computer Science and Engineering & Centre for Health Informatics, University of New South Wales, Sydney

    Ashwin Srinivasan

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Lisi, F.A., Esposito, F. (2004). Efficient Evaluation of Candidate Hypotheses in \(\mathcal{AL}\)-log. In: Camacho, R., King, R., Srinivasan, A. (eds) Inductive Logic Programming. ILP 2004. Lecture Notes in Computer Science(), vol 3194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30109-7_18

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  • DOI: https://doi.org/10.1007/978-3-540-30109-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22941-4

  • Online ISBN: 978-3-540-30109-7

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