CSUSM Experiments in GeoCLEF2005: Monolingual and Bilingual Tasks

  • Rocio Guillén
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


This paper presents the results of our initial experiments in the monolingual English task and the Bilingual Spanish → English task. We used the Terrier Information Retrieval Platform to run experiments for both tasks using the Inverse Document Frequency model with Laplace after-effect and normalization 2. Additional experiments were run with Indri, a retrieval engine that combines inference networks with language modelling. For the bilingual task we developed a component to first translate the topics from Spanish into English. No spatial analysis was carried out for any of the tasks. One of our goals is to have a baseline to compare further experiments with term translation of georeferences and spatial analysis. Another goal is to use ontologies for Integrated Geographic Information Systems adapted to the IR task. Our initial results show that the geographic information as provided does not improve significantly retrieval performance. We included the geographical terms appearing in all the fields. Duplication of terms might have decreased gain of information and affected the ranking.


Information Retrieval Retrieval Performance Short Query Diacritic Mark Geographical Term 
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 2006

Authors and Affiliations

  • Rocio Guillén
    • 1
  1. 1.Computer Science DepartmentCalifornia State University San MarcosUSA

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