A fuzzy inference method for spam-mail filtering
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, JW | - |
dc.contributor.author | Kang, SJ | - |
dc.contributor.author | Kim, BM | - |
dc.date.available | 2020-04-24T14:25:53Z | - |
dc.date.created | 2020-04-03 | - |
dc.date.issued | 2005 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/3381 | - |
dc.description.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. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.title | A fuzzy inference method for spam-mail filtering | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, BM | - |
dc.identifier.wosid | 000235836100150 | - |
dc.identifier.bibliographicCitation | AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE, v.3809, pp.1112 - 1115 | - |
dc.citation.title | AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE | - |
dc.citation.volume | 3809 | - |
dc.citation.startPage | 1112 | - |
dc.citation.endPage | 1115 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalClass | 1 | - |
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