Text mining for indexing

Judith Gelernter, Michael Lesk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationJCDL'09 - Proceedings of the 2009 ACM/IEEE Joint Conference on Digital Libraries
Pages467
Number of pages1
DOIs
StatePublished - 2009
Event2009 ACM/IEEE Joint Conference on Digital Libraries, JCDL'09 - Austin, TX, United States
Duration: Jun 15 2009Jun 19 2009

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries

Other

Other2009 ACM/IEEE Joint Conference on Digital Libraries, JCDL'09
Country/TerritoryUnited States
CityAustin, TX
Period6/15/096/19/09

ASJC Scopus subject areas

  • Engineering(all)

Keywords

  • Classification
  • Geographic information retrieval
  • Ontology
  • Text mining

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