Advances In Spam Filtering Techniques

dc.creatorAlmeida T.A.
dc.creatorYamakami A.
dc.date2012
dc.date2015-06-25T20:25:53Z
dc.date2015-11-26T15:22:59Z
dc.date2015-06-25T20:25:53Z
dc.date2015-11-26T15:22:59Z
dc.date.accessioned2018-03-28T22:32:05Z
dc.date.available2018-03-28T22:32:05Z
dc.identifier9783642252365
dc.identifierStudies In Computational Intelligence. , v. 394, n. , p. 199 - 214, 2012.
dc.identifier1860949X
dc.identifier10.1007/978-3-642-25237-2_12
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84856484509&partnerID=40&md5=f76fed8e2b95ad44b9081cd4676922b0
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/90561
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/90561
dc.identifier2-s2.0-84856484509
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1260441
dc.descriptionNowadays e-mail spam is not a novelty, but it is still an important rising problem with a big economic impact in society. Fortunately, there are different approaches able to automatically detect and remove most of those messages, and the best-known ones are based on machine learning techniques, such as Naïve Bayes classifiers and Support Vector Machines. However, there are several different models of Naïve Bayes filters, something the spam literature does not always acknowledge. In this chapter, we present and compare seven different versions of Naïve Bayes classifiers, the well-known linear Support Vector Machine and a new method based on the Minimum Description Length principle. Furthermore, we have conducted an empirical experiment on six public and real non-encoded datasets. The results indicate that the proposed filter is easy to implement, incrementally updateable and clearly outperforms the state-of-the-art spam filters. © 2012 Springer-Verlag Berlin Heidelberg.
dc.description394
dc.description
dc.description199
dc.description214
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dc.languageen
dc.publisher
dc.relationStudies in Computational Intelligence
dc.rightsfechado
dc.sourceScopus
dc.titleAdvances In Spam Filtering Techniques
dc.typeActas de congresos


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