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IMPROVING THE PERFORMANCE OF ANTI-SPAM FILTERS USING OUT-OF-VOCABULARY STATISTICS

dc.creatorAgüero,Pablo Daniel
dc.creatorCastiñeira Moreira,Jorge
dc.creatorLiberatori,Monica
dc.creatorBonadero,Juan Carlos
dc.creatorTulli,Juan Carlos
dc.date2009-12-01
dc.date.accessioned2019-04-24T21:28:03Z
dc.date.available2019-04-24T21:28:03Z
dc.identifierhttps://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-33052009000300012
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/58586
dc.descriptionThis paper presents a feature based on out-of-vocabulary word statistics that complements the information sources used in the decision by state-of-the-art spam filters. The experiments included freely available spam filters as reference, SpamAssassin, Bogofilter, SpamBayes and SpamProbe, as well as a Naive Bayes classifier. The results show that the decision based on the proposed feature improves the performance of all spam filters under study.
dc.formattext/html
dc.languageen
dc.publisherUniversidad de Tarapacá.
dc.relation10.4067/S0718-33052009000300012
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceIngeniare. Revista chilena de ingeniería v.17 n.3 2009
dc.subjectSpam
dc.subjectfiltering
dc.subjectout-of-vocabulary
dc.titleIMPROVING THE PERFORMANCE OF ANTI-SPAM FILTERS USING OUT-OF-VOCABULARY STATISTICS


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