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On the Efficient Execution of ProbLog Programs

  • Angelika Kimmig
  • Vítor Santos Costa
  • Ricardo Rocha
  • Bart Demoen
  • Luc De Raedt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5366)

Abstract

The past few years have seen a surge of interest in the field of probabilistic logic learning or statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with mutually independent probabilities that they belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Angelika Kimmig
    • 1
  • Vítor Santos Costa
    • 2
  • Ricardo Rocha
    • 2
  • Bart Demoen
    • 1
  • Luc De Raedt
    • 1
  1. 1.Departement ComputerwetenschappenK.U. LeuvenHeverleeBelgium
  2. 2.CRACS & Faculdade de CiênciasUniversidade do Porto, PortugalPortoPortugal

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