The Impact of the Mode of Data Representation for the Result Quality of the Detection and Filtering of Spam

Reda Mohamed Hamou and Abdelmalek Amine
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Reda Mohamed Hamou: Computer Science Department, Dr Moulay Tahar University of Saïda, Saïda, Algeria
Abdelmalek Amine: Computer Science Department, Dr Moulay Tahar University of Saïda, Saïda, Algeria

International Journal of Information Retrieval Research (IJIRR), 2013, vol. 3, issue 1, 43-59

Abstract: Spam is now seized of the Internet in phenomenal proportions since it high represents a percentage of total emails exchanged on the Internet. In the fight against spam, the authors are interested in this article to develop a hybrid algorithm based primarily on the probabilistic model in this case Naïve Bayes for weighting the terms of the matrix term -category and second place used an algorithm of unsupervised learning (K-means) to filter two classes namely spam and ham. To determine the sensitive parameters that improve the classifications the authors are interested in studying the content of the messages by using a representation of messages by the n-gram words and characters independent of languages (because a message may be received in any language) to later decide what representation opt to get a good classification. The authors have chosen several metrics evaluation to validate their results.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:3:y:2013:i:1:p:43-59

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