Computer and Modernization ›› 2020, Vol. 0 ›› Issue (07): 61-64.doi: 10.3969/j.issn.1006-2475.2020.07.012

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Short Text Sentiment Analysis Based on Self-attention and Capsule Network

  

  1. (College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, China)
  • Online:2020-07-06 Published:2020-07-15

Abstract: Sentiment analysis of short texts is a challenging task. Aiming at the shortcomings of traditional convolutional neural networks and recurrent neural networks that can not fully obtain the semantic information contained in texts, this paper proposed a model that used the multi-head self-attention layer as the feature extractor and used the capsule network as the classification layer. The model can extract rich text information and has strong expressive ability. Experimental results on Chinese text showed that compared with the traditional deep learning method, the proposed model improved the accuracy of sentiment analysis. In the small dataset and cross-domain migration, compared with traditional method, the accuracy was greatly improved.

Key words: emotional analysis, self-attention mechanism, capsule network, small datasets learning, migration learning

CLC Number: