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- W904823170 abstract "In this paper, we constructed a spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the legitimate mil. The definite information is the mail sender's information, URL, a certain spam keyword list, and the less definite information is the word lists and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning. According to our results the spam precision was increased if more lexical information was used as features, and the spam recall was increased when the concept codes were included in features as well." @default.
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- W904823170 date "2006-01-01" @default.
- W904823170 modified "2023-09-28" @default.
- W904823170 title "Spam-mail Filtering based on Lexical Information and Thesaurus" @default.
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