A Method of Spam Filtering Based on Weighted Support Vector Machines

摘要：

The problem of content-based spam filtering on machine learning methods actually is a binary classification. SVMs can separate the data into two categories optimally so SVMs suit to spam filtering. With used into spam filtering, the standard support vector machine involves the minimization of the error function and the accuracy of the SVM is very high, but the degree of misclassification of legitimate emails is high. In order to solve that problem, this paper proposed a method of spam filtering based on weighted support vector machines. Experimental results show that the algorithm can enhance the filtering performance effectively.

作者: CHEN Xiao-li LIU Pei-yu ZHU Zhen-fang QIU Ye

作者单位: Department of Information Science and Engineering, Shandong Normal University, Jinan ,250014, China Department of Information Science and Engineering, Shandong Normal University, Jinan , 250014, Chin

会议类型: 国际会议

会议名称: 2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)

会议地点: 济南

会议语种:英文

页码: 947-950

在线出版日期: 2009-08-14（万方平台首次上网日期，不代表论文的发表时间）