The Datalog Combination of Deduction Rules and Description Logics

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Journal titleComputational Intelligence Journal
Subjecthybrid rules; description logic; Datalog; tableaux algorithms; SLD-resolution.
AbstractUniting ontologies and rules has become a central topic in the Semantic Web. Bridging the discrepancy between these two knowledge representations, this paper introduces DatalogDL as a family of hybrid languages, where Datalog rules are parameterized by various DL (description logic) languages ranging from ALC to SHIQ. Making DatalogDL a decidable system with complexity of EXPTIME, we propose independent properties in the DL body as the restriction to hybrid rules, and weaken the safeness condition to balance the trade-off between expressivity and reasoning power. Building on existing well-developed techniques, we present a principled approach to enrich (RuleML) rules with information from (OWL) ontologies, and develop a prototype system combining a rule engine (OO jDREW) with a DL reasoner (RACER).
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number49822
NPARC number9167858
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Record identifier41fb36b7-3390-4e77-9c56-fca6dbef2a1a
Record created2009-06-29
Record modified2016-05-09
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