计算机科学 ›› 2019, Vol. 46 ›› Issue (9): 223-228.doi: 10.11896/j.issn.1002-137X.2019.09.033
孙中锋, 王静
SUN Zhong-feng, WANG Jing
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。
中图分类号:
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