ADDING PROBABILITIES AND RULES TO OWL LITE SUBSETS BASED ON PROBABILISTIC DATALOG

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Abstract
This paper proposes two probabilistic extensions of variants of the OWL Lite description language, which are essential for advanced applications like information retrieval. The first step follows the axiomatic approach of combining description logics and Horn clauses: Subsets of OWL Lite are mapped in a sound and complete way onto Horn predicate logics (Datalog variants). Compared to earlier approaches, a larger fraction of OWL Lite can be transformed by switching to Datalog with equality in the head; however, some OWL Lite constructs cannot be transformed completely into Datalog. By using probabilistic Datalog, the new probabilistic OWL Lite subsets (both with support for Horn rules) are defined, and the semantics are given by the semantics of the corresponding probabilistic Datalog program. As inference engines for probabilistic Datalog are available, description logics and information retrieval systems can easily be combined.

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