LSSVM-based social spam detection model

摘要：

　　To Resolve the garbage tag issue in Folksonomy,Lssvm algorithm for social spa m detection model (least Squares support vector machine classifiers) was proposed.The met hod of inequality change the constraints in the traditional support vector machine into equa lity constraints,and take the empirical function of the squared error loss function as the E xperience function in training set.so that the quadratic programming problem convert QP i nto solving linear equations,it was improving solution the speed of solution and accuracy o f convergence.The experimental results show that we have got higher classification accuracy and less predict time than traditional svm detection methods based on least squares support vector machine algorithm garbage tag detection model.

关键词： social spam social bookmark system Issvm detection model

作者: Xiaolei Yang Yidan Su JinPing Mo

作者单位: Guangxi University of Finance and Economics,Nanning,China Guangxi University, Nanning,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Systems Engineering and Modeling(ICSEM-13)(2013年第二届系统工程与建模国际会议)

会议地点: 北京

会议语种:英文

页码: 7-12

在线出版日期: 2013-04-19（万方平台首次上网日期，不代表论文的发表时间）