Exploiting multiple semantic features for comment text topic clustering
Yahong Li · Computer Engineering and Applications Journal · 2013
The feature is a key to the tasks of emotional analysis and opinion mining.Particularly for unsupervised text clustering task,the text feature quality directly affects the clustering results.This paper studies three kinds of semantic features,namely nouns features,noun phrase features,semantic role features and their role on the text topic clustering.And considering the compatibility between the different features,a method is proposed to eliminate redundant features.The method can effectively remove redundant features to improve the clustering accuracy.Also another method is proposed based on semantic role labeling to directly and effectively locate word features for topic clustering.The experimental results indicate that the method is direct and effective,and a new approach to feature selection method is provided.