Consistent Answers in Probabilistic Datalog+/– Ontologies

Abstract

The Datalog+/– family of ontology languages is especially useful for representing and reasoning over lightweight ontologies, and has many applications in the context of query answering and information extraction for the Semantic Web. It is widely accepted that it is necessary to develop a principled way to handle uncertainty in this domain. In addition to uncertainty as an inherent aspect of the Web, one must also deal with forms of uncertainty due to inconsistency. In this paper, we take an important step in this direction by developing inconsistency-tolerant semantics for query answering in a probabilistic extension of Datalog+/–. The main contributions of this paper are: (i) extension and generalization to probabilistic ontologies of the well-known concepts of repairs and consistent answers to queries from databases; (ii) complexity analysis for the problems of consistency checking, repair identification, and consistent query answering; and (iii) adaptation of the intersection semantics (a sound heuristic for consistent answers) to probabilistic ontologies, yielding a subset of probabilistic Datalog+/– that is tractable modulo the cost of computing probabilities.