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|Type:||Artigo de evento|
|Title:||An Immunological Filter For Spam|
De Castro L.N.
Von Zuben F.J.
|Abstract:||Spam messages are continually filling email boxes of practically every Web user. To deal with this growing problem, the development of high-performance filters to block those unsolicited messages is strongly required. An Antibody Network, more precisely SRABNET (Supervised Real-Valued Antibody Network), is proposed as an alternative filter to detect spam. The model of the antibody network is generated automatically from the training dataset and evaluated on unseen messages. We validate this approach using a public corpus, called PU1, which has a large collection of encrypted personal e-mail messages containing legitimate messages and spam. Finally, we compared the performance with the well known naïve Bayes filter using some performances indexes that will be presented. © Springer-Verlag Berlin Heidelberg 2006.|
|Citation:||Lecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). , v. 4163 LNCS, n. , p. 446 - 458, 2006.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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