Computer Science ›› 2018, Vol. 45 ›› Issue (12): 142-147.doi: 10.11896/j.issn.1002-137X.2018.12.022

• Artificial Intelligence • Previous Articles     Next Articles

Study on Recursive Auto-encoding Sentiment Classification Based on Topic Enhancement

ZHU Yin, HUANG Hai-yan   

  1. (School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)
  • Received:2017-11-07 Online:2018-12-15 Published:2019-02-25

Abstract: The emotional analysis of Chinese text aims to discover the emotional tendencies of users to things and events,however,the existing studies often neglect the interrelationships between texts.In light of this,this paper proposed a recursive auto-encoding classification model based on topic enhancement.By incorporating the subject information of the text into the recursive auto-encoding model,this model can further consider the content information of the text and improve the capability to understand the text emotion and generaliza ability.The experimental results on the COAE2014 dataset show that the proposed classification model can achieve better classification performance when used for tasks of sentiment classification,thus verifying its applicability and feasibility in practical problems.

Key words: Recursive auto-encoder, Topic model, Sentiment classification, Data mining

CLC Number: 

  • TP391
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