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Design, implementation, and evaluation of a methodology for automatic stemmer generation

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  • Massimo Melucci
  • Nicola Orio

Abstract

The authors describe a statistical approach based on hidden Markov models (HMMs), for generating stemmers automatically. The proposed approach requires little effort to insert new languages in the system even if minimal linguistic knowledge is available. This is a key advantage especially for digital libraries, which are often developed for a specific institution or government because the program can manage a great amount of documents written in local languages. The evaluation described in the article shows that the stemmers implemented by means of HMMs are as effective as those based on linguistic rules.

Suggested Citation

  • Massimo Melucci & Nicola Orio, 2007. "Design, implementation, and evaluation of a methodology for automatic stemmer generation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(5), pages 673-686, March.
    • Handle: RePEc:bla:jamist:v:58:y:2007:i:5:p:673-686
    DOI: 10.1002/asi.20509
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