Handling implicit geographic evidence for geographic ir

ABSTRACT

Most geographic information retrieval systems depend on the detection and disambiguation of place names in documents, assuming that the documents with a specific geographic scope contain explicit place names in the text that are strongly related to the document scopes. However, some non-geographic names such as companies, monuments or sport events, may also provide indirect relevant evidence that can significantly contribute to the assignment of geographic scopes to documents. In this paper, we analyze the amount of implicit and explicit geographic evidence in newspaper documents, and measure its impact on geographic information retrieval by evaluating the performance of a retrieval system using the GeoCLEF evaluation data.

REFERENCES

• 1: Sören Auer , Jens Lehmann, What Have Innsbruck and Leipzig in Common? Extracting Semantics from Wiki Content, Proceedings of the 4th European conference on The Semantic Web: Research and Applications, June 03-07, 2007, Innsbruck, Austria [doi>10.1007/978-3-540-72667-8_36]
• 2: N. Cardoso, P. Sousa, and M. J. Silva. The University of Lisbon at GeoCLEF 2008. In F. Borri et al., editors, Working notes of CLEF 2008, Aarhus, Denmark, 17-19 September 2008.
• 3: Diana Santos , Cláudia Freitas , Hugo Gonçalo Oliveira , Paula Carvalho, Second HAREM: New Challenges and Old Wisdom, Proceedings of the 8th international conference on Computational Processing of the Portuguese Language, September 08-10, 2008, Aveiro, Portugal [doi>10.1007/978-3-540-85980-2_22]
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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software

General Terms:
Algorithms, Design

Keywords:
geographic information retrieval, named entity recognition, wikipedia mining