A fuzzy inference method for spam-mail filtering

Authors:
Jong-Wan Kim;Sin-Jae Kang;Byeong Man Kim
Affiliations:
School of Computer and Information Technology, Daegu University, Gyeonsan, Gyeongbuk, South Korea;School of Computer and Information Technology, Daegu University, Gyeonsan, Gyeongbuk, South Korea;School of Computer Engineering, Kumoh National Institute of Technology, Gumi, Gyungbuk, South Korea
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

This paper gives a comparative study of feature selection methods in spam-mail filtering. In our experiment, the fuzzy inference method showed about 6% and 10% improvements over information gain and χ2-test as a feature selection method in terms of the average error rate which is more important than typical information retrieval measures. Since it is not easy to reduce error rate, our work can be regarded as a meaningful research for email users suffering from unsolicited emails flooding indiscriminately.