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

AGUERO, P.; CASTIÑEIRA MOREIRA, J.; LIBERATORI, M. C.; BONADERO, J. C.; TULLI, J. C.

Valdivia, Chile

Congreso; SENACITEL; 2008

This 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 other 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.