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\iteman{io-port 06094700}
\itemau{Du, Fang; Chen, Yueguo; Du, Xiaoyong}
\itemti{Partitioned indexes for entity search over RDF knowledge bases.}
\itemso{Lee, Sang-goo (ed.) et al., Database systems for advanced applications. 17th international conference, DASFAA 2012, Busan, South Korea, April 15--19, 2012. Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-29037-4/pbk). Lecture Notes in Computer Science 7238, 141-155 (2012).}
\itemab
Summary: The rapid growth of RDF data in RDF knowledge bases calls for efficient query processing techniques. This paper focuses on the star-style SPARQL join queries, which is very common when users want to search information of entities from RDF knowledge bases. We observe that the computational cost of such queries mainly comes from loading a large portion of predicate-ahead indexes. We therefore propose to partition the whole RDF knowledge bases based on the schema of individual entities, so that only entities of similar schemas are allocated into the same cluster. Such a partitioning strategy generates a pruning mechanism that effectively isolate the correlations of partitions and the queries. Consequently, queries are only conducted over a small number of partitions with small predicate-ahead indexes. Experiments over a large real-life RDF data set show the significant performance improvements achieved by our partitioned indexing techniques.
\itemrv{~}
\itemcc{}
\itemut{entity search; SPARQL query; index; clustering}
\itemli{doi:10.1007/978-3-642-29038-1\_12}
\end