A fuzzy inference method for spam-mail filtering
- Authors
- Kim, JW; Kang, SJ; Kim, 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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Collections - Department of Computer Software Engineering > 1. Journal Articles
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