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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 5
1416-1421

Research on aspect sentiment triplet extraction based on MUBTM

Ge Jikea
Cheng Wenjuna
Wu Chengzhia
Chen Zuqinb
Dong Yana
a. School of Intelligent Technology & Engineering, b. Library, Chongqing University of Science & Technology, Chongqing 401331, China
DOI: 10.19734/j.issn.1001-3695.2022.09.0468

Abstract

Aspect sentiment triplet extraction aims to identify aspect terms, comment opinion terms and sentiment polarities from comment texts. In view of the existing studies, it is easy to ignore the association relationship between some entities and their sentiment polarities in the triplet, and often occurs the errors in recognizing the boundary of the triplets. This paper proposed a multi-category unification and boundary tagging model based on table filling(MUBTM) by using the category of the sub-elements. Firstly, the model used biaffine attention mechanism to learn the interaction among word pairs, and constructed a multi-category unification tagging space. Next, it adopted the symmetry structural constraints and the cascading binary boundary constraints of the tag space to restrict the probability distribution among word pairs. Finally, according to the property that the sub-elements were square or rectangular in the unified tag spaces, gradually decoded and generated aspect sentiment triplets. Experimental results show that, compared with the baseline models, the proposed model significantly raises the F1 value of aspect sentiment triplet extraction, indicating the feasibility of the proposed method.

Foundation Support

国家社会科学基金西部项目(19XTQ010)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.09.0468
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 5
Section: Algorithm Research & Explore
Pages: 1416-1421
Serial Number: 1001-3695(2023)05-020-1416-06

Publish History

[2022-12-09] Accepted Paper
[2023-05-05] Printed Article

Cite This Article

葛继科, 程文俊, 武承志, 等. 基于MUBTM的方面词情感三元组抽取方法研究 [J]. 计算机应用研究, 2023, 40 (5): 1416-1421. (Ge Jike, Cheng Wenjun, Wu Chengzhi, et al. Research on aspect sentiment triplet extraction based on MUBTM [J]. Application Research of Computers, 2023, 40 (5): 1416-1421. )

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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