Applying NLP Techniques for Query Reformulation to Information Retrieval with Geographical References

  • José M. Perea-Ortega
  • Miguel A. García-Cumbreras
  • L. Alfonso Ureña-López
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7769)

Abstract

Geographic Information Retrieval (GIR) is an active and growing research area that focuses on the retrieval of textual documents according to a geographical criteria of relevance. However, since a GIR system can be treated as a traditional Information Retrieval (IR) system, it is important to pay attention to finding effective methods for query reformulation. In this way, the search results will improve their quality and recall. In this paper, we propose different Natural Language Processing (NLP) techniques of query reformulation related to the modification and/or expansion of both parts thematic and geospatial that are usually recognized in a geographical query. We have evaluated each of the reformulations proposed using GeoCLEF as an evaluation framework for GIR systems. The results obtained show that all proposed query reformulations retrieved relevant documents that were not retrieved using the original query.

Keywords

Geographic query reformulation Geographic Information Retrieval Query expansion GeoCLEF 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • José M. Perea-Ortega
    • 1
  • Miguel A. García-Cumbreras
    • 2
  • L. Alfonso Ureña-López
    • 2
  1. 1.Languages and Information Systems DepartmentUniversity of Sevilla, E.T.S. Ingeniería InformáticaSevillaSpain
  2. 2.Computer Science DepartmentUniversity of Jaén Escuela Politécnica SuperiorJaénSpain

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