Issue No. 11 - November (2010 vol. 22)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.111
Thomas Lukasiewicz , University of Oxford, Oxford
We present a novel combination of disjunctive programs under the answer set semantics with description logics for the Semantic Web. The combination is based on a well-balanced interface between disjunctive programs and description logics, which guarantees the decidability of the resulting formalism without assuming syntactic restrictions. We show that the new formalism has very nice semantic properties. In particular, it faithfully extends both disjunctive programs and description logics. Furthermore, we describe algorithms for reasoning in the new formalism, and we give a precise picture of its computational complexity. We also define the well-founded semantics for the normal case, where normal programs are combined with tractable description logics, and we explore its semantic and computational properties. In particular, we show that the well-founded semantics approximates the answer set semantics. We also describe algorithms for the problems of consistency checking and literal entailment under the well-founded semantics, and we give a precise picture of their computational complexity. As a crucial property, in the normal case, consistency checking and literal entailment under the well-founded semantics are both tractable in the data complexity, and even first-order rewritable (and thus can be done in LogSpace in the data complexity) in a special case that is especially useful for representing mappings between ontologies.
Description logic programs, disjunctive logic programs, normal logic programs, answer set semantics, well-founded semantics, description logics, Semantic Web, algorithms, complexity, first-order rewritability.
Thomas Lukasiewicz, "A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web", IEEE Transactions on Knowledge & Data Engineering, vol. 22, no. , pp. 1577-1592, November 2010, doi:10.1109/TKDE.2010.111