计算机科学 ›› 2019, Vol. 46 ›› Issue (9): 223-228.doi: 10.11896/j.issn.1002-137X.2019.09.033

• 人工智能 • 上一篇    下一篇

用于基于方面情感分析的RCNN-BGRU-HN网络模型

孙中锋, 王静   

  1. (南京工业大学计算机科学与技术学院 南京211816)
  • 收稿日期:2018-07-18 出版日期:2019-09-15 发布日期:2019-09-02
  • 通讯作者: 王 静(1982-),女,副研究员,主要研究领域为无线传感器网络技术,E-mail:wj_cec@126.com
  • 作者简介:孙中锋(1991-),男,硕士生,主要研究领域为机器学习与深度学习;
  • 基金资助:
    南京工业大学引进人才启动基金项目(39809110)

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

摘要: 针对一般神经网络模型在处理基于方面情感分析任务中存在的句子间相互联系少以及单词之间的语义信息获取有限等问题,文中提出了一种新型结构的深度学习网络模型。该模型通过区域卷积神经网络(RCNN)可以很好地保留评论文本中句子的时序关系,同时结合双向门控循环单元(BGRU)可以大大降低模型训练的时间代价。此外,加入的高速公路网络(HN)使得该模型能够捕获更多单词间的语义信息;利用注意力机制来分配网络结构中特定方面的权重,可以有效获取特定方面在整个评论文本中的长距离依赖关系。该模型可以进行端到端的训练,在不同的数据集上取得了比现有网络模型更好的分类效果。

关键词: 高速公路网络, 基于方面情感分析, 卷积神经网络, 深度学习, 双向门控循环单元, 注意力机制

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

中图分类号: 

  • TP183
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