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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 3
676-681

Sentiment analysis model of opinion triplet based on position information

Jiang Yutong
Qian Xuezhong
Song Wei
School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2022.07.0370

Abstract

There are two kinds of tasks in aspect-based sentiment analysis: one is extraction task, which aims to extract aspect words and opinion words from sentences. The other is the classification task, which aims to analyze the sentimental polarity. On the basis of these two complex tasks, aiming at the problem that the coupling between aspect words and opinion words is poor, which leads to the error of classification task, this paper proposed an opinion triplet sentiment analysis model(OTPM) integrating position information. The model used bi-directional long short-term memory network to obtain the text representation, then used the self attention mechanism to enhance the correlation between aspect words and opinion words, and then extracted the opinion triplet in the multi task framework. At the same time, it conducted weighted fusion of extracted representation and position information. Finally, the experiment used biaffine scorer to analyze the sentimental dependence between the weighted aspect words and opinion words, and then used stop-on-non-I algorithm to decode the triplet and output the triplet. This paper conducted a lot of experiments on Lap14, Rest14, Rest15, Rest16 dataset. The results show that the proposed model is superior to a series of baseline models.

Foundation Support

国家自然科学基金项目(62076110)
江苏省自然科学基金项目(BK20181341)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0370
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 3
Section: Algorithm Research & Explore
Pages: 676-681
Serial Number: 1001-3695(2023)03-006-0676-06

Publish History

[2022-10-13] Accepted Paper
[2023-03-05] Printed Article

Cite This Article

姜宇桐, 钱雪忠, 宋威. 融合位置信息的观点三元组情感分析模型 [J]. 计算机应用研究, 2023, 40 (3): 676-681. (Jiang Yutong, Qian Xuezhong, Song Wei. Sentiment analysis model of opinion triplet based on position information [J]. Application Research of Computers, 2023, 40 (3): 676-681. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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