Research of identifying Splog based on multiple structure features
Hongye Tan · Jisuanji gongcheng yu sheji · 2010
To address the growing problem of Splog,the generating Splog technology and the corresponding recognition technology are studied.By analyzing a large number of Chinese Splog and the purposes of Splog maker,a method of extracting feature from blog structure features is proposed such as the user’s name,post time interval,post content,anchor text and link address,classification labels.Based on the feature extraction,a method based on the multiple structure features is proposed.The naive Bayesian model and support vector machines are used as the classifier in our model.Experiments on a small train dataset show that the method based on multiple structure features reaches an accuracy of 90%.Compared with the contend based method,proposed method increases the accuracy by 6%,indicating that the method can identify Splogs effectively.