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Context-Dependent OWL Reasoning in Sindice - Experiences and Lessons Learnt

  • Renaud Delbru
  • Giovanni Tummarello
  • Axel Polleres
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6902)

Abstract

The Sindice Semantic Web index provides search capabilities over 260 million documents. Reasoning over web data enables to make explicit what would otherwise be implicit knowledge: it adds value to the information and enables Sindice to ultimately be more competitive in terms of precision and recall. However, due to the scale and heterogeneity of web data, a reasoning engine for the Sindice system must (1) scale out through parallelisation over a cluster of machines; and (2) cope with unexpected data usage. In this paper, we report our experiences and lessons learned in building a large scale reasoning engine for Sindice. The reasoning approach has been deployed, used and improved since 2008 within Sindice and has enabled Sindice to reason over billions of triples.

Keywords

Reasoning Engine Ontology Base Ontology Context Blank Node Deductive Closure 
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 2011

Authors and Affiliations

  • Renaud Delbru
    • 1
  • Giovanni Tummarello
    • 1
  • Axel Polleres
    • 1
    • 2
  1. 1.Digital Enterprise Research InstituteNational University of Ireland, GalwayGalwayIreland
  2. 2.Siemens AG ÖsterreichViennaAustria

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