DocumentCode
1938754
Title
Statistical Machine Learning Used in Integrated Anti-Spam System
Author
Zhang, Peng-Fei ; Su, Yu-Jie ; Wang, Cong
Volume
7
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
4055
Lastpage
4058
Abstract
IASS is the integrated anti-spam system, which adopts machine learning to filter spam in a intelligent, flexible, precise, and self-adaptive way. The methods of linear classification based on optimal separating hyperplane and K-means clustering are used in action recognition layer. The method of improved naive Bayes is used in content analysis layer. The application of machine learning helps improve the performance of IASS.
Keywords
Bayes methods; Internet; computer crime; information filtering; learning (artificial intelligence); pattern classification; pattern clustering; unsolicited e-mail; Internet; K-means clustering; action recognition layer; content analysis layer; integrated antispam system; linear classification; machine learning; naive Bayes method; spam filtering; statistical machine learning; Cybernetics; Electronic mail; Filters; Frequency; Intelligent networks; Learning systems; Machine learning; Postal services; Protection; Unsolicited electronic mail; Action recognition; Anti-spam system; Machine learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370855
Filename
4370855
Link To Document