Title :
Statistical Machine Learning Used in Integrated Anti-Spam System
Author :
Zhang, Peng-Fei ; Su, Yu-Jie ; Wang, Cong
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;
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
DOI :
10.1109/ICMLC.2007.4370855
