Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2695-2700,2716

Handling contrastive sentences in sentiment analysis based on attention network

Zhang Rong1,2
Liu Yuan2
Li Yang1
1. School of Internet of Things Engineering, Jiangsu Vocational College of Information Technology, Wuxi Jiangsu 214153, China
2. School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2022.02.0052

Abstract

Aspect-level sentiment analysis aims to determine the sentiment polarity towards specific aspect in reviews. However, little research has been done on the influence of complex sentences on sentiment classification. Based on this, this paper proposed an aspect sentiment classification model based on BERT and self-attention network with relative position. Firstly, it used the dynamic weighted sampling method to balance the rare contrastive sentences, so that the model could learn more contrastive sentence feature information. Then, it jointly trained the feature representations extracted by double-head self-attention network with relative position and the feature representations obtained by the pre-trained model with absolute position. Finally, it used the label smoothing regularization technology to stabilize the model to identify the neutral samples. This paper tested this model on Sub Task 2 in SemEval 2014 task, and improved both accuracy and macro-F1 indicators of the two datasets. The experimental results show that the effectiveness of the proposed model for contrastive sentences classification, and also yield improvements in the whole test set over other benchmark models.

Foundation Support

国家自然科学基金资助项目(61972182)
江苏省高等职业教育高水平专业群建设项目(苏教职函〔2021〕1号)
江苏省职业教育教师教学创新团队资助项目(苏教办师函〔2021〕23号)
江苏高校“青蓝工程”资助项目(苏教师函〔2021〕11号)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.02.0052
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Algorithm Research & Explore
Pages: 2695-2700,2716
Serial Number: 1001-3695(2022)09-021-2695-06

Publish History

[2022-04-24] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

张蓉, 刘渊, 李阳. 基于注意力网络的情感分析中的对比句处理 [J]. 计算机应用研究, 2022, 39 (9): 2695-2700,2716. (Zhang Rong, Liu Yuan, Li Yang. Handling contrastive sentences in sentiment analysis based on attention network [J]. Application Research of Computers, 2022, 39 (9): 2695-2700,2716. )

About the Journal

  • 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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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