Text Sentiment Classification Based on Mutual Information and Cluster Sampling
To divide the text sentiment into finer categories,proposes a text sentiment classification method by using mutual information and cluster sampling.Uses the text pre-processing for text segmentation and feature extraction,and calculates the mutual information of each sentiment tag by cluster sampling.Obtains sentiment categories by combination of sentiment tags,and adjusts the weight of key word by mutual information.Derives the text sentiment classification by using center metric.Compares different text sentiment classification in the experiment.The results show that the proposed classification method outperforms other classification methods and verify the effectiveness of the proposed method.
NETL
NSTL
万方数据
维普
