IMPROVING THE PERFORMANCE OF ANTI-SPAM FILTERS USING OUT-OF-VOCABULARY STATISTICS
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 freely available spam filters as reference, SpamAssassin, Bogofilter, SpamBayes and SpamProbe, as well as...
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| Autores principales: | , , , , |
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| Lenguaje: | English |
| Publicado: |
Universidad de Tarapacá.
2009
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| Materias: | |
| Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052009000300012 |
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| Sumario: | 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 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. |
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