Title :
Research on spam filtering technology using Support Vector Machine
Author :
Zheng Mei ; Geng Ji ; Li Xiao ; Liu Qiao
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
Support Vector Machine is a novel machine learning method based on statistical learning theory, and it has been successfully applied to spam filtering system. This paper gives a research to Mail-head Character Categorization using Support Vector Machine(SVM).A total of 106 features were extracted and the filtering performance is good. And the training time is substantially reduced because of the lower dimensional feature space. Finally we implement an automatic Mail-head Character Categorization system, and it also gives the test results.
Keywords :
character recognition; information filtering; learning (artificial intelligence); support vector machines; unsolicited e-mail; SVM; automatic mail-head character categorization system; feature extraction; machine learning method; spam filtering technology; statistical learning theory; support vector machine; Libraries; Training;
Conference_Titel :
Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on
Conference_Location :
Kokura
Print_ISBN :
978-1-4244-1473-4
DOI :
10.1109/ICCCAS.2007.6251613