An Improved SVM-KNN Spam Filtering Approach

摘要：

A novel feature weighted SVM-KNN spam filtering algorithm is proposed,which trains SYM respectively according to the different lengths of samples feature and acquires different weights of different lengths of samples feature in KNN sample library-.KNN classifies the testing samples with the acquired weights.Experiments demonstrate the new algorithm has better accuracy of spam filtering with lower computational burden compared with general SVM-KNN.

关键词： SVM SVM-KN Feature length weighted Spam filtering

作者: Qiao Yan Chengchao Leng

作者单位: College of Computer and software Shenzhen University Shen zhen,China College of Information Engineering Shenzhen University Shen zhen,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 493-496

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）