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BUNDLE: A Reasoner for Probabilistic Ontologies

  • Fabrizio Riguzzi
  • Elena Bellodi
  • Evelina Lamma
  • Riccardo Zese
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7994)

Abstract

Representing uncertain information is very important for modeling real world domains. Recently, the DISPONTE semantics has been proposed for probabilistic description logics. In DISPONTE, the axioms of a knowledge base can be annotated with a set of variables and a real number between 0 and 1. This real number represents the probability of each version of the axiom in which the specified variables are instantiated. In this paper we present the algorithm BUNDLE for computing the probability of queries from DISPONTE knowledge bases that follow the \(\mathcal{ALC}\) semantics. BUNDLE exploits an underlying DL reasoner, such as Pellet, that is able to return explanations for queries. The explanations are encoded in a Binary Decision Diagram from which the probability of the query is computed. The experiments performed by applying BUNDLE to probabilistic knowledge bases show that it can handle ontologies of realistic size and is competitive with the system PRONTO for the probabilistic description logic P-\(\mathcal{SHIQ}\)(D).

Keywords

Logic Program Description Logic Predicate Logic Binary Decision Diagram Expansion Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fabrizio Riguzzi
    • 1
  • Elena Bellodi
    • 2
  • Evelina Lamma
    • 2
  • Riccardo Zese
    • 2
  1. 1.Dipartimento di Matematica e InformaticaUniversity of FerraraFerraraItaly
  2. 2.Dipartimento di IngegneriaUniversity of FerraraFerraraItaly

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