Towards Content-Aware SPARQL Query Caching for Semantic Web Applications

  • Yanfeng Shu
  • Michael Compton
  • Heiko Müller
  • Kerry Taylor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8180)


Applications are increasingly using triple stores as persistence backends, and accessing large amounts of data through SPARQL endpoints. To improve query performance, this paper presents an approach that reuses results of cached queries in a content-aware way for answering subsequent queries. With a focus on a common class of conjunctive SPARQL queries with filter conditions, not only does the paper provide an efficient method for testing whether a query can be evaluated on the result of a cached query, but it also shows how to evaluate the query. Experimental results show the effectiveness of the approach.


Partial Mapping Solution Mapping Cache Size Conjunctive Query SPARQL Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yanfeng Shu
    • 1
  • Michael Compton
    • 1
  • Heiko Müller
    • 1
  • Kerry Taylor
    • 1
  1. 1.Computational InformaticsCSIROAustralia

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