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A fuzzy inference method for spam-mail filtering

Authors
Kim, JWKang, SJKim, BM
Issue Date
2005
Publisher
SPRINGER-VERLAG BERLIN
Citation
AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE, v.3809, pp.1112 - 1115
Journal Title
AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE
Volume
3809
Start Page
1112
End Page
1115
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/3381
ISSN
0302-9743
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 X-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.
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College of Engineering (Department of Computer Software Engineering)
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