Simulation Study on Intelligent Model for Spam Filtering
Sun Xi-bin · Jisuanji fangzhen · 2013
Research on spam filtering accuracy problems.Email is a high-dimensional,complex special text,single support vector machine,K nearest neighbors and other traditional models are difficult to identify spam filter,so the accuracy is very low.In order to improve the spam filtering accuracy,this paper presented a spam filtering model based on K neighbor and support vector machine(SVM-KNN).Firstly,the mail feature vectors were input to a support vector machine to learn and find support vector set,and then the distance of recognition mail and the optimal hyper plane was calculated.If distance is greater than the threshold,support vector machine was used to identify the email type,otherwise K nearest neighbor was used to identify the email type.The simulation results show that the proposed model is a good solution for single model problems and improve the spam filtering accuracy,so SVM-KNN is an effective management means.