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Algorithm Research & Explore
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2328-2333

Multi-relationship collaborative learning model for aspect extraction

Xu Fu
Huang Xianying
Jiang Xingyu
Peng Jingyao
School of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China

Abstract

In recent years, aspect-level sentiment analysis has been widely used in product evaluation, catering, e-commerce decision-making, etc. A core point of this task is aspect word extraction. At present, the commonly used method is to use opinion words to assist in extracting aspect words to mark the text sequence, or to use span notation to predict the beginning and ending positions of aspect words. These methods do not consider the influence of opinion word extraction and emotion polarity classification on aspect word extraction. Aiming at this problem, this paper proposed a multi-relationship collaborative learning model for aspect extraction, which used opinion word extraction, aspect word extraction, and relationship modeling between emotion polarity classification to achieve multi-task collaborative learning and joint training in relationships. The experimental results on the three datasets of REST14, REST15 and LAP14 show that the proposed method is better than the current state-of-the-art method.

Foundation Support

国家自然科学基金资助项目(17XXW005)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.12.0412
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 8
Section: Algorithm Research & Explore
Pages: 2328-2333
Serial Number: 1001-3695(2021)08-014-2328-06

Publish History

[2021-08-05] Printed Article

Cite This Article

徐福, 黄贤英, 蒋兴渝, 等. 用于方面提取的多元关系协作学习模型 [J]. 计算机应用研究, 2021, 38 (8): 2328-2333. (Xu Fu, Huang Xianying, Jiang Xingyu, et al. Multi-relationship collaborative learning model for aspect extraction [J]. Application Research of Computers, 2021, 38 (8): 2328-2333. )

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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