통계적 기법을 이용한 스팸메시지 필터링 기법
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김성윤 | - |
dc.contributor.author | 차태수 | - |
dc.contributor.author | 박제원 | - |
dc.contributor.author | 최재현 | - |
dc.contributor.author | 이남용 | - |
dc.date.available | 2018-05-09T12:01:59Z | - |
dc.date.created | 2018-04-17 | - |
dc.date.issued | 2014-09 | - |
dc.identifier.issn | 1975-4256 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/10518 | - |
dc.description.abstract | Due to indiscriminately received spam messages on information society, spam messages cause damages not only to person but also to our community. Nowadays a lot of spam filtering techniques, such as blocking characters, are studied actively. Most of these studies are content-based spam filtering technologies through machine learning.. Because of a spam message transmission techniques are being developed, spammers have to send spam messages using term spamming techniques. Spam messages tend to include number of nouns, using repeated words and inserting special characters between words in a sentence. In this paper, considering three features, SPSS statistical program were used in parameterization and we derive the equation. And then, based on this equation we measured the performance of classification of spam messages. The study compared with previous studies FP-rate in terms of further minimizing the cost of product was confirmed to show an excellent performance. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 한국IT서비스학회 | - |
dc.relation.isPartOf | 한국IT서비스학회지 | - |
dc.subject | Machine Learning | - |
dc.subject | Spam Message | - |
dc.subject | SPSS | - |
dc.subject | Logistic Regression | - |
dc.title | 통계적 기법을 이용한 스팸메시지 필터링 기법 | - |
dc.title.alternative | A Technique of Statistical Message Filtering for Blocking Spam Message | - |
dc.type | Article | - |
dc.identifier.doi | 10.9716/KITS.2014.13.3.299 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | 한국IT서비스학회지, v.13, no.3, pp.299 - 308 | - |
dc.identifier.kciid | ART001918068 | - |
dc.description.journalClass | 2 | - |
dc.citation.endPage | 308 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 299 | - |
dc.citation.title | 한국IT서비스학회지 | - |
dc.citation.volume | 13 | - |
dc.contributor.affiliatedAuthor | 박제원 | - |
dc.contributor.affiliatedAuthor | 최재현 | - |
dc.contributor.affiliatedAuthor | 이남용 | - |
dc.identifier.url | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001918068 | - |
dc.description.isOpenAccess | N | - |
dc.description.oadoiVersion | published | - |
dc.subject.keywordAuthor | Machine Learning | - |
dc.subject.keywordAuthor | Spam Message | - |
dc.subject.keywordAuthor | SPSS | - |
dc.subject.keywordAuthor | Logistic Regression | - |
dc.description.journalRegisteredClass | kci | - |
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