Relaxing feature selection in spam filtering by using case-based reasoning systems

Authors:
J. R. Méndez;F. Fdez-Riverola;D. Glez-Peña;F. Díaz;J. M. Corchado
Affiliations:
Dept. Informática, University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Ourense, Spain;Dept. Informática, University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Ourense, Spain;Dept. Informática, University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Ourense, Spain;Dept. Informática, University of Valladolid, Escuela Universitaria de Informática, Segovia, Spain;Dept. Informática y Automática, University of Salamanca, Salamanca, Spain
Venue:
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Year:
2007

Citing 7
Cited 0

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Abstract

This paper presents a comparison between two alternative strategies for addressing feature selection on a well known case-based reasoning spam filtering system called SPAMHUNTING. We present the usage of the k more predictive features and a percentage-based strategy for the exploitation of our amount of information measure. Finally, we confirm the idea that the percentage feature selection method is more adequate for spam filtering domain.