The Impact of Noise in Spam Filtering: A Case Study

  • I. Cid
  • L. R. Janeiro
  • J. R. Méndez
  • D. Glez-Peña
  • F. Fdez-Riverola
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5077)


Unsolicited commercial e-mail (UCE), more commonly known as spam is a growing problem on the Internet. Every day people receive lots of unwanted advertising e-mails that flood their mailboxes. Fortunately, there are several approaches for spam filtering able to detect and automatically delete this kind of messages. However, spammers have adopted some techniques to reduce the effectiveness of these filters by introducing noise in their messages. This work presents a new pre-processing technique for noise identification and reduction, showing preliminary results when it is applied with a Flexible Bayes classifier. The experimental analysis confirms the advantages of using the proposed technique in order to improve spam filters accuracy.


Feature Selection Mutual Information Feature Selection Method Document Frequency Feature Selection Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • I. Cid
    • 1
  • L. R. Janeiro
    • 1
  • J. R. Méndez
    • 1
  • D. Glez-Peña
    • 1
  • F. Fdez-Riverola
    • 1
  1. 1.Dept. InformáticaUniversity of Vigo, Escuela Superior de Ingeniería Informática Edificio PolitécnicoOurenseSpain

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