Computer Science ›› 2019, Vol. 46 ›› Issue (9): 223-228.doi: 10.11896/j.issn.1002-137X.2019.09.033

• Artificial Intelligence • Previous Articles     Next Articles

RCNN-BGRU-HN Network Model for Aspect-based Sentiment Analysis

SUN Zhong-feng, WANG Jing   

  1. (School of Computer Science and Technology,Nanjing Tech University,Nanjing 211816,China)
  • Received:2018-07-18 Online:2019-09-15 Published:2019-09-02

Abstract: The general neural network model has less inter-connectivity between sentences and cannot capture much more semantic information between words in the task of aspect-based sentiment analysis.To adress these problems,this paper proposed a deep learning network model with novel structure.The model can preserve the sequential relationship of sentences in the comment text through the regional convolutional neural network(RCNN).At the same time,the time cost of model training can be greatly reduced by combining bi-directional gated recurrent unit (BGRU).In addition,the introduction of highway network (HN) could enable the proposed model to capture much more semantic information between words.The attention mechanism is additionally utilized in an effort to assign weights of the concerned aspect in the network structure,which is able to effectively obtain the long-distance dependency of the concerned aspect in the whole review.The model can give end-to-end training and experiment on different datasets,achieving better performance than the existing network model.

Key words: Aspect-based sentiment analysis, Attention mechanism, Bi-directional gated recurrent unit, Convolutional neural network, Deep learning, Highway network

CLC Number: 

  • TP183
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