An approach to automatic classification of text for information retrieval

Research output: Contribution to conferencePaper

5 Scopus citations

Abstract

In this paper, we explore an approach to make better use of semi-structured documents in information retrieval in the domain of biology. Using machine learning techniques, we make those inherent structures explicit by XML markups. This marking up has great potentials in improving task performance in specimen identification and the usability of online flora and fauna.

Original languageEnglish (US)
Pages96-97
Number of pages2
StatePublished - Dec 1 2002
Externally publishedYes
EventProceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries - Portland, OR, United States
Duration: Jul 14 2002Jul 18 2002

Other

OtherProceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries
CountryUnited States
CityPortland, OR
Period7/14/027/18/02

Keywords

  • Automatic classification
  • Flora of North America
  • Machine learning
  • XML

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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  • Cite this

    Cui, H., Heidorn, P. B., & Zhang, H. (2002). An approach to automatic classification of text for information retrieval. 96-97. Paper presented at Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries, Portland, OR, United States.