Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 3
704-710

Aspect-level sentiment analysis based on double-layer part-of-speech-aware and multi-head interactive attention mechanism

Xue Fang1
Guo Yi1,2,3
Li Zhiqiang1
Wang Jiahui1
1. Dept. of Computer Science & Engineering, East China University of Science & Technology, Shanghai 200237, China
2. Business Intelligence & Visualization Research Center, National Engineering Laboratory for Big Data Distribution & Exchange Technologies, Shanghai 200436, China
3. Shanghai Engineering Research Center of Big Data & Internet Audience, Shanghai 200072, China
DOI: 10.19734/j.issn.1001-3695.2021.08.0340

Abstract

In aspect-level sentiment analysis research, previous work often ignores the problem that the contribution of different types of parts of speech and the interaction of local and global features affects the classification accuracy. This paper proposed an aspect-level sentiment analysis model DPMHA based on double-layer part-of-speech-aware and multi-head interactive attention mechanism. Firstly, this paper used BERT pre-training model to obtain word vectors of contextual information. Secondly, this paper creatively proposed two part-of-speech-aware local feature extraction layers, which could focus on these words around aspect words with important parts of speech and reduce the influence of noise words. Then, this paper designed a multi-head interactive attention mechanism between local features and global features to fully explore the important interactive features between them. Finally, this paper also proposed a dynamic feature fusion layer and softmax layer to obtain the results of sentiment analysis. Experiments on three public data set show that compared with the existing aspect-level sentiment analysis model, the DPMHA model increases the MF1 value of the restaurant14, laptop14, and restaurant15 datasets by 2.41%, 1.24% and 2.39% respectively, and the accuracy rate increases by 1.34%, 0.78% and 0.37% respectively.

Foundation Support

国家重点研发计划资助项目(2018YFC0807105)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0340
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 3
Section: Algorithm Research & Explore
Pages: 704-710
Serial Number: 1001-3695(2022)03-010-0704-07

Publish History

[2021-11-15] Accepted Paper
[2022-03-05] Printed Article

Cite This Article

薛芳, 过弋, 李智强, 等. 基于双层词性感知和多头交互注意机制的方面级情感分析 [J]. 计算机应用研究, 2022, 39 (3): 704-710. (Xue Fang, Guo Yi, Li Zhiqiang, et al. Aspect-level sentiment analysis based on double-layer part-of-speech-aware and multi-head interactive attention mechanism [J]. Application Research of Computers, 2022, 39 (3): 704-710. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)