Spam message filtering based on dependency grammar
Jun Yi · Journal of Beijing University of Chemical Technology · 2013
In view of the flood of spam short message,a dependency relation based Chinese short message classification approach was proposed in this paper. In this approach,through short text syntax analyzing,words with strong dependency relation were combined into new features,and then these new features were used to classify the short text through text classification algorithm. The relationship of different words was considered in the feature selection method based on the dependency grammar. Dependency relation based approach used a more suitable way,which was better in keeping with people thinking and incorporating some semantic information,to extract short text features. Experimental results showed that the proposed approach in this paper had better classification effects compared with traditional approaches.