Experiments with Geo-Filtering Predicates for IR

  • Jochen L. Leidner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


This paper describes a set of experiments for monolingual English retrieval at Geo-CLEF 2005, evaluating a technique for spatial retrieval based on named entity tagging, toponym resolution, and re-ranking by means of geographic filtering. To this end, a series of systematic experiments in the Vector Space paradigm are presented. Plain bag-of-words versus phrasal retrieval and the potential of meronymy query expansion as a recall-enhancing device are investigated, and three alternative geo-spatial filtering techniques based on spatial clipping are compared and evaluated on 25 monolingual English queries. Preliminary results show that always choosing toponym referents based on a simple “maximum population” heuristic to approximate the salience of a referent fails to outperform TF*IDF baselines with the Geo-CLEF 2005 dataset when combined with three geo-filtering predicates. Conservative geo-filtering outperforms more aggressive predicates. The evidence further seems to suggest that query expansion with WordNet meronyms is not effective in combination with the method described. A post-hoc analysis indicates that responsible factors for the low performance include sparseness of available population data, gaps in the gazetteer that associates Minimum Bounding Rectangles with geo-terms in the query, and the composition of the Geo-CLEF 2005 dataset itself.


Digital Library Query Expansion Relevance Assessment Minimum Bounding Rectangle Aggressive Predicate 
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

  • Jochen L. Leidner
    • 1
    • 2
    • 3
  1. 1.Linguit GmbHBad BergzabernGermany
  2. 2.University of the Saarland, FR 7.4 – Speech Signal ProcessingSaarbrückenGermany
  3. 3.School of InformaticsUniversity of EdinburghEdinburghScotland, UK

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