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demonstration

Text mining for indexing

Published: 15 June 2009 Publication History

Abstract

This paper describes techniques for automatically extracting and classifying maps found within articles. The process uses image analysis to find text in maps, document structure to find captions and titles, and then text mining to assign each map to a subject category, a geographical place, and a time period. The text analysis is based on authority lists taken from gazetteers and from library classifications.

References

[1]
Borges, K. A., Laender, A. H., Medeiros, C. B., and Davis, C. A. 2007. Discovering geographic locations in web pages using urban addresses. In Proceedings of the 4th ACM Workshop on Geographical information Retrieval (Lisbon, Portugal, November 09 -- 09, 2007). GIR '07. ACM, New York, NY, 31--36. DOI= http://doi.acm.org/10.1145/1316948.1316957
[2]
Leidner, J. 2007. Toponym Resolution in Text. SIGIR Forum, 41 (2): 125. Dec. 2007.
[3]
Sanderson, M. and Kohler, J. 2004. Analyzing geographic queries. Proceedings of Workshop on Geographic Information Retrieval SIGIR, 2004 Retrieved January 22, 2009 from http://dis.shef.ac.uk/mark/publications/my_papers/GeoQueryAn alysis2004.pdf

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Published In

cover image ACM Conferences
JCDL '09: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
June 2009
502 pages
ISBN:9781605583228
DOI:10.1145/1555400

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 June 2009

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Author Tags

  1. automatic classification
  2. content analysis and indexing
  3. text mining

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  • Demonstration

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JCDL '09
JCDL '09: Joint Conference on Digital Libraries
June 15 - 19, 2009
TX, Austin, USA

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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