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一种复合的双引擎智能垃圾邮件过滤方法 被引量:1

Intelligent and integrated method of spam filtering with double engines
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摘要 研究了几种常用的垃圾邮件过滤算法,分析了这几种方法在邮件过滤应用中各自的优缺点。根据这几种算法的优缺点,对它们进行改良与结合,并增加了通过查看发出的邮件内容进行自动学习的机制;同时针对中英文垃圾邮件采用不同的学习算法,从而建立一个适用中英文环境的垃圾邮件过滤方法。实验表明,该方法的效率和性能达到了较好的水平。 This paper studied several popular algorithms for spam filtering. All of them had different advantages and disadvantages: some good at Chinese, and some good at English. By integrating and improving these algorithms, presented an intelligent method of spam filtering. This method utilized the advantages of previous algorithms and avoided their shortages. Moreover, it also added an intelligent mechanism which could self-study by using the contents of the emails. Finally, it is found that this algorithm do well in the real environments.
出处 《计算机应用研究》 CSCD 北大核心 2008年第1期268-270,302,共4页 Application Research of Computers
关键词 垃圾邮件 正常邮件 黑白名单 规则 贝叶斯过滤算法 spam mail ham mail white and black lists rules Bayesian filtering
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参考文献6

  • 1GRAHAM P.A plan for spam[EB/OL].(2002-10-14).http://www.paulgraham.com/spam.html.
  • 2GRAHAM P.A better Bayesian filtering[EB/OL].(2003-10-14).http://www.paulgraham.com/better.html.
  • 3SOONTHORNPHISAJ N,CHAIKULSERIWAT K,PIYANAN T O.Anti-spam filtering:a centroid-based classification approach[C]//Proc of the 6th International Conference on Signal Processing.2002:1096-1099.
  • 4吴立德.独立于语种的文本分类算法[C]//Proc of 2000 International Conference on Multilingual Information Processing.2000:37-43.
  • 5张晓冬,张书杰,邢俊丽,李俊玉.关于信息过滤模型的探讨[J].计算机工程与应用,2002,38(5):99-100. 被引量:18
  • 6CHANG K C,FUNG R M.Target identification with Bayesian networks in a multiple hypothesis tracking system[J].IEEE Trans Optical Engineering,1997,36(3):684-691.

二级参考文献13

  • 1[1]Faloutsos C,Oard D W.A Survey of Information Retrieval and Fil tering Methods.http : //www.cs.umd.edu/
  • 2[2]Gerard Salton,Edward A Fox,Harry Wu.Extended Boolean Information Retrieval[J].Communications of the ACM, 1983;26(12): 1022-1036
  • 3[3]Tak W Yan,Hector Carcia_Molina. Index Structures for InformationFiltering Under the Vector Space Model.http://www.enee.umd.edu/
  • 4[5]Foltz P W,Dumais S T.Personalized information delivery:an Analysisof Information filtering methods[J].Communications of the ACM, 1992;35(12) :51-60
  • 5[6]Yan T W,Gracia_Molina H.Index Structures for information filtering under the vector space model[R].Technical Report STAN CS 93 1491 ,Stanford University, 1993
  • 6[7]Foltz P W.Using Latent Semantic Indexing for Information Filtering[C].In:R B Allen Ecl.Proceeding of the Conference on Office InformationSystems, Cambridge, MA: 40-47
  • 7[8]Deerwester S,Dumais D T,Furnas G W et al.Indexing by Latent Semantic Analysis[J].Joumal of the American ,Society for Information Science, 1990;46(6) ) :391-407
  • 8[9]Howard R Turtle,W Bruce Croft. A Comparison of Text Retrieval Models[J].The Computer Journal, 1992; 35 ( 3 )
  • 9[10]Donna Harman,Christos Faloutsos,Susan Dumais et al.lnformation Filtering and Retrieval :Overview ,Issues and Directions Basis for a Panel Discussion.http://www.glue.umd.edu/
  • 10[11]Foltz P W.Latent Semantic Analysis for Text-Based Research Behavior Research Methods[J].Instruments and Computers, 1996;28(2):197-202

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