Computer Science ›› 2018, Vol. 45 ›› Issue (12): 153-159.doi: 10.11896/j.issn.1002-137X.2018.12.024

• Artificial Intelligence • Previous Articles     Next Articles

Multi-granularity Sentiment Classification Method Based on Sequential Three-way Decisions

ZHANG Gang-qiang, LIU Qun, JI Liang-hao   

  1. (Chongqing Key Laboratory of Computational Intelligence,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
  • Received:2017-12-13 Online:2018-12-15 Published:2019-02-25

Abstract: How to classify the review data correctly is important research content in sentiment analysis.From the perspective of granular computing and cognitive science,this paper proposed a multi-granularity sentiment classification method for Chinese reviews based on sequential three-way decisions.Firstly,based on the characteristics of review data,a coarse-to-fine multi-granularity sentiment information representation method is put forward according to the amounts of sentiment information existing in the review.Then,by combining the principle of sequential three-way decisions,the calculation is gradually executed in different sentiment information granularity and the sequenced three-way decision is carried out for the boundary reviews.Lastly,according to the decision thresholds and costs in different granularities,the final sentiment classification is provided for the review data.The experimental results show that the proposed method achieves better performance,and performes higher classification accuracy and stronger robustness on three classic datasets.

Key words: Sentiment classification, Sequential three-way decisions, Multi-granularity, Cognitive

CLC Number: 

  • TP391
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