JISE


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Journal of Information Science and Engineering, Vol. 39 No. 4, pp. 855-868


Classify Text-based Email Using Naive Bayes Method With Small Sample


YANJUN ZHU1, TING ZHU2,+, JIANXIN LI3,8, WENLIANG CAO4,
PENG YONG5, FEI JIANG6 AND JIE LIU7
1,3,4,5,7School of Electronic Information
Dongguan Polytechnic, Dongguan, 523808 China
E-mail: Zhuyanjun073@163.com
1; 279149042@qq.com3; caowl22@163.com4;
pengy@dgpt.edu.cn
5; 1123261349@qq.com7
2Department of Information Engineering
Gannan University of Science and Technology
Ganzhou, Jiangxi, 341000 China
E-mail: tingzhu915@163.com

6School of Modern Circulation, Guang Xi International Business Vocational College, Nanning, China
School of Management and Marketing, Taylors University, Malaysia

8Department of Public Relations
Guangdong Only Network Science and Technology Co., Ltd., 523000 China
E-mail: 279149042@qq.com


With the popularity of the Internet, e-mail has gradually become one of the important communication tools for people’s work and life with its fast and convenient advantages. However, the problem of spam has become increasingly serious. It not only spreads harm-ful information, but also consumes a lot of public resources and infringes the legitimate rights and interests of e-mail users and enterprises. Although there are many spam filtering methods at present, the situation that spam does not fall but rises shows that the existing spam filtering methods have not achieved ideal filtering effect. This paper uses naive Bayesian method and small sample to classify e-mail, and combines Chinese information processing technology to propose an efficient filtering system BETSY. The experimental results show that the method proposed in this paper has achieved good results and has direct application value.


Keywords: Naïve Bayes, classifier, E-mail classification, filtering system, small sample

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