Matches in ScholarlyData for { ?s ?p Description Logic Programs (DL-programs) have been introduced as a realization of combined ontological and rule-based reasoning in the context of the Semantic Web. A DL-program loosely combines a Description Logic (DL) ontology with a non-monotonic logic program (LP) such that dedicated atoms in the LP, called DL-atoms, allow for a bidirectional flow of knowledge between the two components. Unfor- tunately, the information sent from the LP-part to the DL-part might cause an inconsistency in the latter, leading to the trivial satisfaction of every query. As a consequence, in such a case, the answer sets that define the semantics of the DL-program may contain spoiled informa- tion influencing the overall deduction. For avoiding unintuitive answer sets, we introduce a refined semantics for DL-programs that is sensitive for inconsistency caused by the combination of DL and LP, and dynam- ically deactivates rules whenever such an inconsistency would arise. We analyze the complexity of the new semantics, discuss implementational issues and introduce an adequate notion of stratification that guarantees uniqueness of answer sets.. }
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- 66 abstract "Description Logic Programs (DL-programs) have been introduced as a realization of combined ontological and rule-based reasoning in the context of the Semantic Web. A DL-program loosely combines a Description Logic (DL) ontology with a non-monotonic logic program (LP) such that dedicated atoms in the LP, called DL-atoms, allow for a bidirectional flow of knowledge between the two components. Unfor- tunately, the information sent from the LP-part to the DL-part might cause an inconsistency in the latter, leading to the trivial satisfaction of every query. As a consequence, in such a case, the answer sets that define the semantics of the DL-program may contain spoiled informa- tion influencing the overall deduction. For avoiding unintuitive answer sets, we introduce a refined semantics for DL-programs that is sensitive for inconsistency caused by the combination of DL and LP, and dynam- ically deactivates rules whenever such an inconsistency would arise. We analyze the complexity of the new semantics, discuss implementational issues and introduce an adequate notion of stratification that guarantees uniqueness of answer sets.".