SVM-based social spam detection model
基于支持向量机的垃圾标签检测模型

The popular social bookmarking sites were always attacked by social spam. This paper designed a SVM-based social spam detection model to solve this problem. That was using VSM to build the user model ,and then divided the users of the sites into two classes by SVM, of which one was the normal, the other was spammer. So cut off the social spam by reducing the spammer. The result of the experiment shows that the classification accuracy of SVM-based social spam detection model is higher than others.