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基于多个机器学习算法的投票式邮件过滤模型
引用本文:李永亮,刘海燕,陈军.基于多个机器学习算法的投票式邮件过滤模型[J].计算机工程,2006,32(19):214-216.
作者姓名:李永亮  刘海燕  陈军
作者单位:装甲兵工程学院信息工程系,北京,100072
摘    要:机器学习算法在目前垃圾邮件过滤中扮演着重要的角色,但单一学习算法往往有各自的缺陷,限制了其在邮件过滤中的进一步应用。该文介绍了几种典型机器学习算法,并构造了一种基于多机器学习算法的投票式过滤模型。实验表明,该方法充分利用了各机器学习算法的优势,弥补了各自的不足,达到了比单一学习算法更好的过滤性能。

关 键 词:垃圾邮件  过滤  机器学习  投票
文章编号:1000-3428(2006)19-0214-03
收稿时间:10 13 2005 12:00AM
修稿时间:2005-10-13

Voting E-mail Filter Model Based on Multi-machine Learning Algorithms
LI Yongliang,LIU Haiyan,CHEN Jun.Voting E-mail Filter Model Based on Multi-machine Learning Algorithms[J].Computer Engineering,2006,32(19):214-216.
Authors:LI Yongliang  LIU Haiyan  CHEN Jun
Affiliation:Department of Information Engineering, Armed Forces Academy of Engineering, Beijing 100072
Abstract:The machine learning algorithms play an important role in current spam filter, but a single machine learning algorithm has its own drawback which restrains it from further application in E-mail filter. This paper introduces some typical machine learning algorithms, and constructs a voting E-mail filter model based on multi-machine learning algorithms. The experiments show that this method makes use of every machine learning algorithm’s advantage, and offsets its disadvantage, and achieves better filter performance than a single algorithm.
Keywords:Spam  Filter  Machine learning  Voting
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