Single n-gram stemming

  • Authors:
  • James Mayfield;Paul McNamee

  • Affiliations:
  • The Johns Hopkins University, Laurel MD;The Johns Hopkins University, Laurel MD

  • Venue:
  • Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

Stemming can improve retrieval accuracy, but stemmers are language-specific. Character n-gram tokenization achieves many of the benefits of stemming in a language independent way, but its use incurs a performance penalty. We demonstrate that selection of a single n-gram as a pseudo-stem for a word can be an effective and efficient language-neutral approach for some languages.