Research On Spam Filter Based On Improved Naive Bayes and KNN Algorithm

被引：0
|
作者：
Ren, Biyi [1 ]
Shi, Yuliang [1 ]
机构：
[1] Beijing Univ Technol, Sch Software, Beijing 100124, Peoples R China
来源：
PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY | 2016年 / 60卷
关键词：
spam filter; Naive Bayes; KNN;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the field of data mining and pattern recognition, classification is a very important core technology. This paper present two kinds of improved classification algorithm. Using the improved Naive Bayes (NB) and KNN algorithm structure classifier to filter normal mail and spam. Improved NB algorithm can dynamically adjust the threshold k, reduces the mail mistake rate. Center vector method is introduced into the similarity calculation formula of KNN, better reflect the interrelation between the text and categories. Finally, improvedNB algorithm and KNN algorithm make comparison and analysis, it is concluded that the effective experimental results.
引用
收藏
页码：1113 / 1116
页数：4
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