Testing OWL Axioms against RDF Facts: A Possibilistic Approach

Andrea G. B. Tettamanzi; Catherine Faron Zucker; Fabien Gandon

doi:10.1007/978-3-319-13704-9_39

Testing OWL Axioms against RDF Facts: A Possibilistic Approach

Andrea G. B. Tettamanzi ¹ Catherine Faron Zucker ¹ Fabien Gandon ¹

1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics

CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems

Abstract : Automatic knowledge base enrichment methods rely criti-cally 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 satis-factory 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

Document type :

Conference papers

Domain :

Computer Science [cs] / Artificial Intelligence [cs.AI]

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Cited literature [14 references] Display Hide Download

https://hal.archives-ouvertes.fr/hal-01084444
Contributor : Andrea G. B. Tettamanzi <>
Submitted on : Wednesday, November 19, 2014 - 11:44:43 AM
Last modification on : Monday, November 5, 2018 - 3:52:09 PM
Document(s) archivé(s) le : Friday, April 14, 2017 - 8:16:21 PM

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