Presented at: 9th International Semantic Web Conference (ISWC2010)http://dx.doi.org/10.1007/978-3-642-17746-0_22
In this paper, we discuss optimisations of rule-based materialisation approaches for reasoning over large static RDF datasets. We generalise and reformalise what we call the "partial-indexing" approach to scalable rule-based materialisation: the approach is based on a separation of terminological data, which has been shown in previous and related works to enable highly scalable and distributable reasoning for specific rulesets; in so doing, we provide some completeness propositions with respect to semi-naive evaluation. We then show how related work on template rules - T-Box-specific dynamic rulesets created by binding the terminological patterns in the static ruleset - can be incorporated and optimised for the partial-indexing approach. We evaluate our methods using LUBM(10) for RDFS, pD* (OWL Horst) and OWL 2 RL, and thereafter demonstrate pragmatic distributed reasoning over 1.12 billion Linked Data statements for a subset of OWL 2 RL/RDF rules we argue to be suitable for Web reasoning.
Keywords: semantic web
Resource URI on the dog food server: http://data.semanticweb.org/conference/iswc/2010/paper/305
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