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A Rewriting Algorithm for Inferrable SPARQL Query Processing Independent of Ontology Inference Models  

Jeong, Dong-Won (국립군산대학교 수학정보통계학부)
Jing, Yixin (고려대학교 컴퓨터학과)
Baik, Doo-Kwon (고려대학교 컴퓨터학과)
Publication Information
Journal of KIISE:Databases / v.35, no.6, 2008 , pp. 505-517 More about this Journal
Abstract
This paper proposes a rewriting algorithm of OWL-DL ontology query in SPARQL. Currently, to obtain inference results of given SPARQL queries, Web ontology repositories construct inference ontology models and match the SPARQL queries with the models. However, an inference model requires much larger space than its original base model, and reusability of the model is not available for other inferrable SPARQL queries. Therefore, the aforementioned approach is not suitable for large scale SPARQL query processing. To resolve tills issue, this paper proposes a novel SPARQL query rewriting algorithm that can obtain results by rewriting SPARQL queries and accomplishing query operations against the base ontology model. To achieve this goal, we first define OWL-DL inference rules and apply them on rewriting graph pattern in queries. The paper categorizes the inference rules and discusses on how these rules affect the query rewriting. To show the advantages of our proposal, a prototype system based on lena is implemented. For comparative evaluation, we conduct an experiment with a set of test queries and compare of our proposal with the previous approach. The evaluation result showed the proposed algorithm supports an improved performance in efficiency of the inferrable SPARQL query processing without loss of completeness and soundness.
Keywords
Web ontology; SPARQL; Inference; OWL-DL; Query Rewriting; Graph Pattern; Semantic Web;
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