Algorithm Research & Explore
|
699-703

Relation extraction based on recurrent convolutional neural network

Wan Jing1
Li Haoming1
Yan Huanchun1
Zhang Xuechao2
1. College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China
2. College of Joint Logistics, National Defence University, Beijing 100091, China

Abstract

Most of the relation extraction approaches could not learn the long distance dependence information from the long sentences with entity co-occurrence. This paper proposed a new relation extraction model to solve this problem. It was based on the recurrent convolutional neural network and the sentence-level attention mechanism. It used the Bi-GRU neural network to learn context vectors for words. And it adopted the piecewise maximum pooling method, which could obtain fine grained features. Experimental results on the NYT dataset demonstrate that this proposed method outperforms the baseline systems.

Foundation Support

国家科技支撑计划资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0635
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Algorithm Research & Explore
Pages: 699-703
Serial Number: 1001-3695(2020)03-013-0699-05

Publish History

[2020-03-05] Printed Article

Cite This Article

万静, 李浩铭, 严欢春, 等. 基于循环卷积神经网络的实体关系抽取方法研究 [J]. 计算机应用研究, 2020, 37 (3): 699-703. (Wan Jing, Li Haoming, Yan Huanchun, et al. Relation extraction based on recurrent convolutional neural network [J]. Application Research of Computers, 2020, 37 (3): 699-703. )

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)