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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2014.1
- 수록면
- 299 - 308 (10page)
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초록· 키워드
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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.
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등록된 정보가 없습니다.
참고문헌 (12)
참고문헌 신청
Androutsopoulos, I. / 2000 / An evaluation of naive bayesian anti-spam filtering / Proceedings of the Workshop on Machine Learning in the New Information Age, 11th European Conference on Machine Learning
Bishop, C.M. / 2006 / Pattern Recognition and Machine Learning / Springer-Verlag
Drucker, H. / 1999 / Support vector machines for spam categorization / IEEE Transactions on Neural Networks 10(5)
Duda, R.O. / 2000 / Pattern Classification 2/E / Wiley-Interscience
공미경 / 2008 / 스팸성 자질과 URL 자질의 공동 학습을 이용한 최대 엔트로피 기반 스팸메일 필터 시스템 / 정보처리학회논문지. 소프트웨어 및 데이터 공학 15(1):61~68
Bishop, C.M. / 2006 / Pattern Recognition and Machine Learning / Springer-Verlag
Drucker, H. / 1999 / Support vector machines for spam categorization / IEEE Transactions on Neural Networks 10(5)
Duda, R.O. / 2000 / Pattern Classification 2/E / Wiley-Interscience
공미경 / 2008 / 스팸성 자질과 URL 자질의 공동 학습을 이용한 최대 엔트로피 기반 스팸메일 필터 시스템 / 정보처리학회논문지. 소프트웨어 및 데이터 공학 15(1):61~68
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