In this paper we consider the most common ABox reasoning services for the description logic DL 4LQS R,× (D) (DL 4,× D , for short) and prove their decidability via a reduction to the satisfiability problem for the set-theoretic fragment 4LQS R . The description logic DL 4,× D is very expressive, as it admits various concept and role constructs, and data types, that allow one to represent rule-based languages such as SWRL. Decidability results are achieved by defining a generalization of the conjunctive query answering problem, called HOCQA (Higher Order Conjunctive Query Answering), that can be instantiated to the most widespread ABox reasoning tasks. We also present a KE-tableau based procedure for calculating the answer set from DL 4,× D knowledge bases and higher order DL 4,× D conjunctive queries, thus providing means for reasoning on several well-known ABox reasoning tasks. Our calculus extends a previously introduced KE-tableau based decision procedure for the CQA problem.
In this paper we use results from Computable Set Theory as a means to represent and reason about description logics and rule languages for the semantic web. Specifically, we introduce the description logic DL 4LQS R (D)-admitting features such as min/max cardinality constructs on the left-hand/righthand side of inclusion axioms, role chain axioms, and datatypes-which turns out to be quite expressive if compared with SROIQ(D), the description logic underpinning the Web Ontology Language OWL. Then we show that the consistency problem for DL 4LQS R (D)-knowledge bases is decidable by reducing it, through a suitable translation process, to the satisfiability problem of the stratified fragment 4LQS R of set theory, involving variables of four sorts and a restricted form of quantification. We prove also that, under suitable not very restrictive constraints, the consistency problem for DL 4LQS R (D)-knowledge bases is NP-complete. Finally, we provide a 4LQS R -translation of rules belonging to the Semantic Web Rule Language (SWRL).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.