Tokenising, Stemming and Stopword Removal on Anti-spam Filtering Domain

  • J. R. Méndez
  • E. L. Iglesias
  • F. Fdez-Riverola
  • F. Díaz
  • J. M. Corchado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4177)

Abstract

Junk e-mail detection and filtering can be considered a cost-sensitive classification problem. Nevertheless, preprocessing methods and noise reduction strategies used to enhance the computational efficiency in text classification cannot be so efficient in e-mail filtering. This fact is demonstrated here where a comparative study of the use of stopword removal, stemming and different tokenising schemes is presented. The final goal is to preprocess the training e-mail corpora of several content-based techniques for spam filtering (machine approaches and case-based systems). Soundness conclusions are extracted from the experiments carried out where different scenarios are taken into consideration.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • J. R. Méndez
    • 1
  • E. L. Iglesias
    • 1
  • F. Fdez-Riverola
    • 1
  • F. Díaz
    • 2
  • J. M. Corchado
    • 3
  1. 1.Dept. InformáticaUniversity of Vigo, Escuela Superior de Ingeniería Informática, Edificio PolitécnicoOurenseSpain
  2. 2.Dept. InformáticaUniversity of Valladolid, Escuela Universitaria de InformáticaSegoviaSpain
  3. 3.Dept. Informática y AutomáticaUniversity of SalamancaSalamancaSpain

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