Resolution-Based Approximate Reasoning for OWL DL
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We propose a new technique for approximate ABox reasoning with OWL DL ontologies. Essentially, we obtain substantially improved reasoning performance by disregarding non-Horn features of OWL DL. Our approach comes as a side-product of recent research results concerning a new transformation of OWL DL ontologies into negation-free disjunctive datalog [1, 2, 3, 4], and rests on the idea of performing standard resolution over disjunctive rules by treating them as if they were non-disjunctive ones. We analyse our reasoning approach by means of non-monotonic reasoning techniques, and present an implementation, called SCREECH.
& Vrandecic, D.
(2005). Resolution-Based Approximate Reasoning for OWL DL. Lecture Notes in Computer Science, 3729, 383-397.