BaseVISor: A Triples-Based Inference Engine Outfitted to Process RuleML and R-Entailment Rules

Authors:
Christopher J. Matheus;Ken Baclawski;Mieczyslaw M. Kokar
Affiliations:
Versatile Information Systems, USA;Northeastern University, USA;Northeastern University, USA
Venue:
RULEML '06 Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web
Year:
2006

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Abstract

BaseVISor is a forward-chaining inference engine based on a Rete network optimized for the processing of RDF triples. A clause within the body and head of a rule either represents an RDF triple or invokes a procedural attachment (either built-in or user defined). This paper describes how BaseVISor has been outfitted to process RuleML and R-Entailment rules. In the case of RuleML, n-ary predicates are automatically translated into binary predicates and reified statements that encapsulate the n-ary predicates' arguments. For R-Entailment rules, the appropriate R-Entailment axioms, axiomatic triples and consistency rules are automatically imported into the engine and then used to derive all triples entailed by any set of triples asserted into the fact base. Operation of the system is illustrated using sample rule sets for both RuleML and R-Entailment and instructions are provided on how to obtain the BaseVISor beta release and process the examples.