Testing OWL Axioms against RDF Facts: A Possibilistic Approach

  • Andrea G. B. Tettamanzi
  • Catherine Faron-Zucker
  • Fabien Gandon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8876)

Abstract

Automatic knowledge base enrichment methods rely critically on candidate axiom scoring. The most popular scoring heuristics proposed in the literature are based on statistical inference. We argue that such a probability-based framework is not always completely satisfactory and propose a novel, alternative scoring heuristics expressed in terms of possibility theory, whereby a candidate axiom receives a bipolar score consisting of a degree of possibility and a degree of necessity. We evaluate our proposal by applying it to the problem of testing SubClassOf axioms against the DBpedia RDF dataset.

Keywords

ontology learning open-world assumption possibility theory 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Andrea G. B. Tettamanzi
    • 1
  • Catherine Faron-Zucker
    • 1
  • Fabien Gandon
    • 2
  1. 1.Univ. Nice Sophia Antipolis, I3S, UMR 7271Sophia AntipolisFrance
  2. 2.INRIASophia AntipolisFrance

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