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Content-based mobile spam classification using stylistically motivated features

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dc.contributor.authorSohn, Dae-Neung-
dc.contributor.authorLee, Jung-Tae-
dc.contributor.authorHan, Kyoung-Soo-
dc.contributor.authorRim, Hae-Chang-
dc.date.accessioned2021-09-06T10:21:30Z-
dc.date.available2021-09-06T10:21:30Z-
dc.date.created2021-06-19-
dc.date.issued2012-02-01-
dc.identifier.issn0167-8655-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/106088-
dc.description.abstractThe feature of brevity in mobile phone messages makes it difficult to distinguish lexical patterns to identify spam. This paper proposes a novel approach to spam classification of extremely short messages using not only lexical features that reflect the content of a message but new stylistic features that indicate the manner in which the message is written. Experiments on two mobile phone message collections in two different languages show that the approach outperforms previous content-based approaches significantly, regardless of language. (C) 2011 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER-
dc.subjectNATURAL-LANGUAGE-
dc.titleContent-based mobile spam classification using stylistically motivated features-
dc.typeArticle-
dc.contributor.affiliatedAuthorRim, Hae-Chang-
dc.identifier.doi10.1016/j.patrec.2011.10.017-
dc.identifier.scopusid2-s2.0-84255178470-
dc.identifier.wosid000300135300017-
dc.identifier.bibliographicCitationPATTERN RECOGNITION LETTERS, v.33, no.3, pp.364 - 369-
dc.relation.isPartOfPATTERN RECOGNITION LETTERS-
dc.citation.titlePATTERN RECOGNITION LETTERS-
dc.citation.volume33-
dc.citation.number3-
dc.citation.startPage364-
dc.citation.endPage369-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusNATURAL-LANGUAGE-
dc.subject.keywordAuthorMobile spam classification-
dc.subject.keywordAuthorText messaging service-
dc.subject.keywordAuthorStylistic features-
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