Algorithm Research & Explore
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2292-2296

Target level sentiment classification based on deep memory network

Zuo Mei
Jing Xiaoyuan
School of Computer Science, Wuhan University, Wuhan 430072, China

Abstract

Memory network only focusing on attention mechanism can't tackle this situation where the context sentiment relies on the concrete target. In order to address this problem, this paper proposed a target-sensitive deep memory network model. This model exploited attention mechanism to capture the sentiment information of context corresponding to a given target. Then the interaction module integrated context sentiment expression and interaction information between context and target to the classification features. Finally, it classified the features to get sentiment polarity of target. This paper conducted experiments on the two datasets from SemEval 2014 task4. The proposed model achieved better performance than attention-based memory networks. The experimental results show that considering the interaction between context and target is effective to solve the problem that context sentiment relies on the concrete target.

Foundation Support

国家自然科学基金资助项目(61672208)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.02.0049
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2292-2296
Serial Number: 1001-3695(2020)08-010-2292-05

Publish History

[2020-08-05] Printed Article

Cite This Article

左梅, 荆晓远. 基于深度记忆网络的特定目标情感分类 [J]. 计算机应用研究, 2020, 37 (8): 2292-2296. (Zuo Mei, Jing Xiaoyuan. Target level sentiment classification based on deep memory network [J]. Application Research of Computers, 2020, 37 (8): 2292-2296. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

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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