In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 5
1396-1401

Enhanced canonical polyadic decomposition link prediction embedding method of knowledge graph

Zhao Bo
Wang Yujia
Ni Ji
Institute of Electronic & Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201600, China
DOI: 10.19734/j.issn.1001-3695.2022.09.0498

Abstract

Canonical polyadic decomposition as one of the methods for link prediction of knowledge graphs, enabling link prediction complementation of some knowledge graphs containing regular data. However, when there is a large amount of sparse data and reversible relationships in the knowledge graph, the method cannot reflect the hidden connection between two entities and cannot process such data. To address the above issues, this paper proposed an enhanced canonical polyadic decomposition method to learn the two embedding vectors of the front entity and the back entity in the triad separately, and used probabilistic methods to generate higher quality negative example triads during the training process. It introduced ELU loss function and AMSGrad optimiser to effectively process reversible relationships. Experimental results on the generic dataset show that the proposed method can effectively improve link prediction accuracy, with a 5% performance improvement compared to the comparison model, and is also applied in the complementation of the automotive repair knowledge graph dataset, achieving 83.2% correct entity complementation results.

Foundation Support

国家自然科学基金资助项目(61403249)
科技创新2030-“新一代人工智能”重大项目(2020AAA0109300)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.09.0498
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 5
Section: Algorithm Research & Explore
Pages: 1396-1401
Serial Number: 1001-3695(2023)05-017-1396-06

Publish History

[2023-01-04] Accepted Paper
[2023-05-05] Printed Article

Cite This Article

赵博, 王宇嘉, 倪骥. 知识图谱的增强CP分解链接预测方法 [J]. 计算机应用研究, 2023, 40 (5): 1396-1401. (Zhao Bo, Wang Yujia, Ni Ji. Enhanced canonical polyadic decomposition link prediction embedding method of knowledge graph [J]. Application Research of Computers, 2023, 40 (5): 1396-1401. )

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)