Detecting tag spam in social tagging systems with kernel K-meansclustering and semi-definite programming SVM
用核K-means聚类和半定规划SVM实现垃圾标签检测

This paper presented a method. It used kernel K-means clustering algorithm to extract the character vector set from the samples and got the optimal combinatorial coefficients of different functions to construct semi-definite programming SVM with stronger nonlinear mapping ability. Experimental results on UCI datasets show that compared with double-layer reduction method, the new method gives higher accuracy and speeds up obviously.