Research of a spam filter based on improved naive Bayes algorithm

doi:10.11959/j.issn.2096-109x.2017.00119

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Research of a spam filter based on improved naive Bayes algorithm

academic paper | 更新时间：2024-06-03

- Research of a spam filter based on improved naive Bayes algorithm
- Chinese Journal of Network and Information Security Vol. 3, Issue 3, Pages: 64-70(2017)
- 作者机构：
  
  1. 哈尔滨工程大学计算机科学与技术学院，黑龙江哈尔滨 150001
  2. 东北林业大学机电工程学院，黑龙江哈尔滨 150040
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2017.00119
  CLC： TP319
- Online First：2017-03，
  
  Published：15 March 2017
- 稿件说明：
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Research of a spam filter based on improved naive Bayes algorithm[J]. Chinese Journal of Network and Information Security, 2017, 3(3): 64-70.
DOI：

Research of a spam filter based on improved naive Bayes algorithm[J]. Chinese Journal of Network and Information Security, 2017, 3(3): 64-70. DOI： 10.11959/j.issn.2096-109x.2017.00119.

摘要

研究了基于改进的支持向量机（SVM，support vector machine）算法结合朴素贝叶斯算法在垃圾邮件过滤中的应用。首先，SVM 对训练集样本空间中两类交界处的集合构造一个最优分类超平面；然后，每个样本根据与其最近邻的类型是否相同进行取舍，从而降低样本空间也提高了每个样本类别的独立性；最后，利用朴素贝叶斯算法对邮件分类。仿真实验结果表明，该算法降低了样本空间复杂度，快速得到最优分类特征子集，有效地提高了垃圾邮件过滤的分类速度、准确率和召回率。

Abstract

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.

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references

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