Chinese Journal of Network and Information Security ›› 2017, Vol. 3 ›› Issue (3): 64-70.doi: 10.11959/j.issn.2096-109x.2017.00119

• academic paper • Previous Articles     Next Articles

Research of a spam filter based on improved naive Bayes algorithm


  1. 1 College of Computer Science and Technology,Harbin Engineering University,Harbin 150001,China
    2 College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,China
  • Revised:2016-11-25 Online:2017-03-01 Published:2017-03-25


In spam filtering filed,naive Bayes algorithm is one of the most popular algorithm,a modified using support vector machine(SVM)of the native Bayes algorithm :SVM-NB was proposed.Firstly,SVM constructs an optimal separating hyperplane for training set in the sample space at the junction two types of collection,Secondly,according to its similarities and differences between the neighboring class mark for each sample to reduce the sample space also increase the independence of classes of each samples.Finally,using naive Bayesian classification algorithm for mails.The simulation results show that the algorithm reduces the sample space complexity,get the optimal classification feature subset fast,improve the classification speed and accuracy of spam filtering effectively.

Key words: naive Bayes, SVM, trim, spam mail

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