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GikiCLEF Topics and Wikipedia Articles: Did They Blend?

  • Nuno Cardoso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6241)

Abstract

This paper presents a post-hoc analysis on how the Wikipedia collections fared in providing answers and justifications to GikiCLEF topics. Based on all solutions found by all GikiCLEF participant systems, this paper measures how self-sufficient the particular Wikipedia collections were to provide answers and justifications for the topics, in order to better understand the recall limit that a GikiCLEF system specialised in one single language has.

Keywords

Answer Type Evaluation Track Romanian Writer Questionable Judgement Recall Limit 
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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References

  1. 1.
    Santos, D., Cabral, L.M.: GikiCLEF: Expectations and lessons learned. In: Peters, C., et al. (eds.) CLEF 2009 Workshop, Part I. LNCS, vol. 6241, pp. 212–222. Springer, Heidelberg (2010)Google Scholar
  2. 2.
    Cardoso, N., Baptista, D., Lopez-Pellicer, F.J., Silva, M.J.: Where in the Wikipedia is that answer? the XLDB at the GikiCLEF 2009 task. In: Peters, C., et al. (eds.) CLEF 2009 Workshop, Part I. LNCS, vol. 6241, pp. 305–309. Springer, Heidelberg (2010)Google Scholar
  3. 3.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: A Nucleus for a Web of Open Data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Nuno Cardoso
    • 1
  1. 1.Faculty of Sciences, LaSIGE, and Linguateca, Oslo node, SINTEF ICTUniversity of LisbonNorway

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