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Experiments on the Exclusion of Metonymic Location Names from GIR

  • Johannes Leveling
  • Dirk Veiel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4730)

Abstract

For the GeoCLEF task of the CLEF campaign 2006, we investigate identifying literal (geographic) and metonymic senses of location names (the location name refers to another, related entity) and indexing them differently. In document preprocessing, location name senses are identified with a classifier relying on shallow features only. Different senses are stored in corresponding document fields, i.e. LOC (all senses), LOCLIT (literal senses), and LOCMET (metonymic senses). The classifier was trained on manually annotated data from German CoNLL-2003 data and from a subset of the GeoCLEF newspaper corpus.

The setup of our GIR (geographic information retrieval) system is a variant of our setup for GeoCLEF 2005. Results of the retrieval experiments indicate that excluding metonymic senses of location names (short: metonymic location names) improves mean average precision (MAP). Furthermore, using topic narratives decreases MAP, and query expansion with meronyms improves the performance of GIR in our experiments.

Keywords

Query Expansion Mean Average Precision Entity Recognition Query Text Query Topic 
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 2007

Authors and Affiliations

  • Johannes Leveling
    • 1
  • Dirk Veiel
    • 1
  1. 1.FernUniversität in Hagen (University of Hagen), Intelligent Information and Communication Systems (IICS), 58084 HagenGermany

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