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Testing OWL Axioms against RDF Facts: A Possibilistic Approach
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.
Cited literature [14 references]
https://hal.archives-ouvertes.fr/hal-01084444
Contributor : Andrea G. B. Tettamanzi Connect in order to contact the contributor
Submitted on : Wednesday, November 19, 2014 - 11:44:43 AM
Last modification on : Sunday, May 1, 2022 - 3:15:40 AM
Long-term archiving on: : Friday, April 14, 2017 - 8:16:21 PM
Contributor : Andrea G. B. Tettamanzi Connect in order to contact the contributor
Submitted on : Wednesday, November 19, 2014 - 11:44:43 AM
Last modification on : Sunday, May 1, 2022 - 3:15:40 AM
Long-term archiving on: : Friday, April 14, 2017 - 8:16:21 PM
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