Convolutional Multi-Head Self-Attention on Memory for Aspect Sentiment Classification

doi:10.1109/JAS.2020.1003243

CASIA OpenIR > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	Convolutional Multi-Head Self-Attention on Memory for Aspect Sentiment Classification
	Yaojie Zhang; Bing Xu; Tiejun Zhao
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2020
卷号	7 期号:4 页码:1038-1044
摘要	This paper presents a method for aspect based sentiment classification tasks, named convolutional multi-head self-attention memory network (CMA-MemNet). This is an improved model based on memory networks, and makes it possible to extract more rich and complex semantic information from sequences and aspects. In order to fix the memory network’s inability to capture context-related information on a word-level, we propose utilizing convolution to capture n-gram grammatical information. We use multi-head self-attention to make up for the problem where the memory network ignores the semantic information of the sequence itself. Meanwhile, unlike most recurrent neural network (RNN) long short term memory (LSTM), gated recurrent unit (GRU) models, we retain the parallelism of the network. We experiment on the open datasets SemEval-2014 Task 4 and SemEval-2016 Task 6. Compared with some popular baseline methods, our model performs excellently.
关键词	Aspect sentiment classification deep learning memory network sentiment analysis (SA)
DOI	10.1109/JAS.2020.1003243
引用统计	被引频次：47[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/43011
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Yaojie Zhang,Bing Xu,Tiejun Zhao. Convolutional Multi-Head Self-Attention on Memory for Aspect Sentiment Classification[J]. IEEE/CAA Journal of Automatica Sinica,2020,7(4):1038-1044.
APA	Yaojie Zhang,Bing Xu,&Tiejun Zhao.(2020).Convolutional Multi-Head Self-Attention on Memory for Aspect Sentiment Classification.IEEE/CAA Journal of Automatica Sinica,7(4),1038-1044.
MLA	Yaojie Zhang,et al."Convolutional Multi-Head Self-Attention on Memory for Aspect Sentiment Classification".IEEE/CAA Journal of Automatica Sinica 7.4(2020):1038-1044.

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