RDF Snippets for Semantic Web Search Engines

  • Xi Bai
  • Renaud Delbru
  • Giovanni Tummarello
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5332)


Recently, there has been interest in ranking the resources and generating corresponding expressive descriptions from the Semantic Web. This paper proposes an approach for automatically generating snippets from RDF documents and assisting users in better understanding the content of RDF documents returned by Semantic Web search engines. A heuristic method for discovering topics, based on the occurrences of RDF nodes and the URIs of original RDF documents, is presented and experimented in this paper. In order to make the snippets more understandable, two strategies are proposed and used for ranking the topic-related statements and the query-related statements respectively. Finally, the conclusion is drawn based on the discussion about the performances of our topic discovery and the whole snippet generation approaches on a test dataset provided by Sindice.


Open Linked Data Natural Language Generation Topic Node Digital Enterprise Research Institute Snippet Generation 
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 2008

Authors and Affiliations

  • Xi Bai
    • 1
    • 2
  • Renaud Delbru
    • 1
  • Giovanni Tummarello
    • 1
  1. 1.Digital Enterprise Research InstituteNational University of IrelandGalwayIreland
  2. 2.College of Computer Science and TechnologyJilin UniversityChangchunChina

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