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Machine Learning

, Volume 70, Issue 2–3, pp 151–168 | Cite as

Compressing probabilistic Prolog programs

  • L. De Raedt
  • K. Kersting
  • A. Kimmig
  • K. Revoredo
  • H. Toivonen
Article
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Abstract

ProbLog is a recently introduced probabilistic extension of Prolog (De Raedt, et al. in Proceedings of the 20th international joint conference on artificial intelligence, pp. 2468–2473, 2007). A ProbLog program defines a distribution over logic programs by specifying for each clause the probability that it belongs to a randomly sampled program, and these probabilities are mutually independent. The semantics of ProbLog is then defined by the success probability of a query in a randomly sampled program.

This paper introduces the theory compression task for ProbLog, which consists of selecting that subset of clauses of a given ProbLog program that maximizes the likelihood w.r.t. a set of positive and negative examples. Experiments in the context of discovering links in real biological networks demonstrate the practical applicability of the approach.

Keywords

Probabilistic logic Inductive logic programming Theory revision Compression Network mining Biological applications Statistical relational learning 
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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • L. De Raedt
    • 2
  • K. Kersting
    • 1
  • A. Kimmig
    • 2
  • K. Revoredo
    • 1
  • H. Toivonen
    • 3
  1. 1.Institut für InformatikAlbert-Ludwigs-UniversitätFreiburg im BreisgauGermany
  2. 2.Departement ComputerwetenschappenK.U. LeuvenHeverleeBelgium
  3. 3.Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland

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