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When stopword lists make the difference

Auteur(s)
Dolamic, Ljiljana
Savoy, Jacques 
Institut d'informatique 
Date de parution
2009
In
Journal of the American Society for Information Science and Technology, Wiley, 2009/61/1/200-203
Mots-clés
  • stoplists
  • information retrieval
  • retrieval effectiveness
  • weighting
  • automatic indexing
  • stoplists

  • information retrieval...

  • retrieval effectivene...

  • weighting

  • automatic indexing

Résumé
In this brief communication, we evaluate the use of two stopword lists for the English language (one comprising 571 words and another with 9) and compare them with a search approach accounting for all word forms. We show that through implementing the original Okapi form or certain ones derived from the Divergence from Randomness (DFR) paradigm, significantly lower performance levels may result when using short or no stopword lists. For other DFR models and a revised Okapi implementation, performance differences between approaches using short or long stopword lists or no list at all are usually not statistically significant. Similar conclusions can be drawn when using other natural languages such as French, Hindi, or Persian.
Identifiants
https://libra.unine.ch/handle/123456789/14727
_
10.1002/asi.21186
Type de publication
journal article
Dossier(s) à télécharger
 main article: Dolamic_Ljiljana_-_When_Stopword_Lists_Make_the_Difference_20091218.pdf (273.92 KB)
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