Using Naive Bayes Method to Classify Text-based Email

被引：0
|
作者：
Kang, LanLan [1 ]
Chen, Ruey-Shun [2 ]
Chen, Yeh-Cheng [3 ]
Cao, WenLiang [2 ]
机构：
[1] Jiangxi Univ Sci & Technol, Sch Appl Sci, Ganzhou, Peoples R China
[2] Dongguan Polytech, Dept Comp Engn, Dongguan, Peoples R China
[3] Univ Calif Davis, Dept Comp Sci, Davis, CA 95616 USA
来源：
2018 9TH INTERNATIONAL CONFERENCE ON PARALLEL ARCHITECTURES, ALGORITHMS AND PROGRAMMING (PAAP 2018) | 2018年
基金：
中国国家自然科学基金;
关键词：
Naive Bayes; Classifier; E-mail Classification; Filtering System;
D O I：
10.1109/PAAP.2018.00023
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The World Talk Corporation estimates that over 60 million business people use e-mail. Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. And yet, automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. Here, I attack problems that plague practical e-mail filtering and suggest solutions that will bring us closer to the acceptance of using automated classification techniques to filter personal e-mail. I also present a filtering system, BETSY, that is both effective and efficient, and which has been adapted to a popular e-mail client. Results are presented from a number of experiments and show that a system such as BETSY could become a useful and valuable part of any e-mail client.
引用
收藏
页码：94 / 98
页数：5
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