计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (16): 138-140.DOI: 10.3778/j.issn.1002-8331.2009.16.040

• 数据库、信息处理 • 上一篇    下一篇

粗糙集与决策树在电子邮件分类与过滤中的应用

邓春燕1,3,陶多秀2,吕跃进3   

  1. 1.广西河池学院 计算机与信息科学系,广西 宜州 546300
    2.广西大学 电气工程学院,南宁 530004
    3.广西大学 数学与信息科学学院,南宁 530004
  • 收稿日期:2008-12-15 修回日期:2009-02-25 出版日期:2009-06-01 发布日期:2009-06-01
  • 通讯作者: 邓春燕

Application of rough set and decision tree in e-mail classification and filtering

DENG Chun-yan1,3,TAO Duo-xiu2,LV Yue-jin3   

  1. 1.Department of Computer and Information Science,Hechi University,Yizhou,Guangxi 546300,China
    2.College of Electrical Engineering,Guangxi University,Nanning 530004,China
    3.College of Mathematics and Information Science,Guangxi University,Nanning 530004,China
  • Received:2008-12-15 Revised:2009-02-25 Online:2009-06-01 Published:2009-06-01
  • Contact: DENG Chun-yan

摘要: 垃圾邮件的识别与过滤是目前研究的热点问题之一。而粗糙集是一种新的处理模糊和不确定性知识的数据分析工具,已被成功地应用到许多有关分类的领域。将粗糙集与决策树结合,提出一个基于RS-DT的邮件分类方案与模型,并进行了实验及结果分析。通过与朴素贝叶斯模型及SVM的比较,表明提出的基于RS-DT的模型可以降低把正常邮件错分为垃圾邮件的比率,提高过滤系统的自学习能力。

关键词: 垃圾邮件, 粗糙集, 数据挖掘, 决策树

Abstract: Spam identification and filtering is one of the hot issues.And the rough set is a new data analysis tool to deal with ambiguity and uncertainty of knowledge;it has been successfully applied to many areas of classification.Combining rough sets with decision tree,a spam filtering solution based on rough sets and decision tree(RS-DT) was proposed.The feasibility of the solution was indicated by the experiments on the public email corpus.Comparison experiments were also made between SVM classifier,Bayes classifier and RS-DT model.The results show that the RS-DT model can not only reduce the error rate of judging the normal email as spam,but also improve adaptive learning of the filtration system.

Key words: spam, rough set, data mining, decision tree