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dc.creatorGuzella, Thiago dos Santos-
dc.creatorSantos, Tomaz Aroldo Mota-
dc.creatorCaminhas, Walmir Matos-
dc.creatorUchôa, Joaquim Quinteiro-
dc.date.accessioned2015-05-21T20:44:05Z-
dc.date.available2015-05-21T20:44:05Z-
dc.date.issued2015-05-21-
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/9645-
dc.description.abstractIn this paper, an immune-inspired model, named innate and adaptive artificial immune system (IA-AIS) is proposed and applied to the problem of identification of unsolicited bulk e-mail messages (SPAM). It integrates entities analogous to macrophages, B and T lymphocytes, modeling both the innate and the adaptive immune systems. An implementation of the algorithm was capable of identifying more than 99% of legitimate or SPAM messages in particular parameter configurations. It was compared to an optimized version of the na¨ıve Bayes classifier, which has been attained extremely high correct classification rates. It has been concluded that IA-AIS has a greater ability to identify SPAM messages, although the identification of legitimate messages is not as high as that of the implemented na¨ıve Bayes classifier. © 2008 Elsevier Ireland Ltd. All rights reserved.pt_BR
dc.languageenpt_BR
dc.rightsacesso abertopt_BR
dc.sourceBiosystems, Volume 92, Issue 3, June 2008, Pages 215-225pt_BR
dc.subjectArtificial immune systempt_BR
dc.subjectSPAM identificationpt_BR
dc.subjectContinuous learningpt_BR
dc.subjectInnate and adaptive immunitypt_BR
dc.subjectRegulatory t cellspt_BR
dc.titleIdentification of SPAM messages using an approach inspired on the immune systempt_BR
dc.typeArtigopt_BR
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