Algorithm Research & Explore
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1770-1774

Context-aware learning for aspect category sentiment classification

Wang Jingjing
Jiang Ming
Zhang Min
School of Computer, Hangzhou Dianzi University, Hangzhou 310000, China

Abstract

A review often involves multiple categories and their emotional tendencies, but the traditional attention mechanism is difficult to distinguish the correspondence between aspect words and emotion words, which affects the analysis of emotional polarity when there are multiple aspect categories in a review. In order to solve the above problems, this paper proposed an context aware learning for aspect category sentiment classification model(MA-DSA). The model captured more diverse and effective semantic features in the sentence by reconstructing the aspect vector, and integrated it into the context vector. Then, it used the context vector to further capture the internal emotional characteristics of the sentence through the DiSA module to determine the aspect and emotion words. Then the sentiment classification was performed on the specified aspect category. The experimental results on SemEval's three datasets show that the three index values of MA-DSA on the Restaurant-2014 dataset are better than the baseline model, which proves the effectiveness of this model.

Foundation Support

浙江省科技计划资助项目(2020C03105)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0172
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Algorithm Research & Explore
Pages: 1770-1774
Serial Number: 1001-3695(2021)06-031-1770-05

Publish History

[2021-06-05] Printed Article

Cite This Article

王晶晶, 姜明, 张旻. 基于上下文感知的方面类别情感分类 [J]. 计算机应用研究, 2021, 38 (6): 1770-1774. (Wang Jingjing, Jiang Ming, Zhang Min. Context-aware learning for aspect category sentiment classification [J]. Application Research of Computers, 2021, 38 (6): 1770-1774. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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