Consequence-based reasoning beyond horn ontologies

Authors:
František Simančík;Yevgeny Kazakov;Ian Horrocks
Affiliations:
Department of Computer Science, University of Oxford;Department of Computer Science, University of Oxford;Department of Computer Science, University of Oxford
Venue:
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Year:
2011

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Abstract

Consequence-based ontology reasoning procedures have so far been known only for Horn ontology languages. A difficulty in extending such procedures is that non-Horn axioms seem to require reasoning by case, which causes non-determinism in tableau-based procedures. In this paper we present a consequence-based procedure for ALCH that overcomes this difficulty by using rules similar to ordered resolution to deal with disjunctive axioms in a deterministic way; it retains all the favourable attributes of existing consequence-based procedures, such as goal-directed "one pass" classification, optimal worst-case complexity, and "pay-as-you-go" behaviour. Our preliminary empirical evaluation suggests that the procedure scales well to non-Horn ontologies.