Advertisement

GoRelations: An Intuitive Query System for DBpedia

  • Lushan Han
  • Tim Finin
  • Anupam Joshi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7185)

Abstract

Although a formal query language, SPARQL, is available for accessing DBpedia, it remains challenging for users to query the knowledge unless they are familiar with the syntax of SPARQL and the underlying ontology. We have developed both an intuitive semantic graph notation or interface allowing one to pose a query by annotating a graph with natural language terms denoting entities and relations and a system that automatically translates the query into SPARQL to produce an answer. Our key contributions are the robust techniques, combining statistical association and semantic similarity, that map user terms to the most appropriate classes and properties used in the DBpedia Ontology.

Keywords

Intuitive Query Ontology Mapping Statistical Association 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: A Nucleus for a Web of Open Data. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Lopez, V., Fernndez, M., Motta, E., Stieler, N.: Poweraqua: Supporting users in querying and exploring the semantic web content. Semantic Web Journal (2011)Google Scholar
  3. 3.
    Church, K., Hanks, P.: Word association norms, mutual information and lexicography. In: Proc. 27th Annual Conf. of the ACL, pp. 76–83 (1989)Google Scholar
  4. 4.
    Mihalcea, R., Corley, C., Strapparava, C.: Corpus-based and knowledge-based measures of text semantic similarity. In: Proc. 21st AAAI Conf., pp. 775–780 (2006)Google Scholar
  5. 5.
    Rapp, R.: Word sense discovery based on sense descriptor dissimilarity. In: Proc. 9th Machine Translation Summit, pp. 315–322 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lushan Han
    • 1
  • Tim Finin
    • 1
  • Anupam Joshi
    • 1
  1. 1.University of MarylandBaltimore CountyUSA

Personalised recommendations