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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 1
47-51,56

Prediction of inductive relationship based on BERT and path contrast learning

Yin Xi
Liang Jingzhang
School of Electrical Engineering, Guangxi University, Nanning 530004, China
DOI: 10.19734/j.issn.1001-3695.2022.05.0253

Abstract

In previous knowledge graph relationship prediction tasks, the main approach is straightforward reasoning, which couldn't use a priori knowledge to deal with inductive learning in the case of unseen entities and relations. This paper proposed a relationship prediction method based on BERT and path contrast learning, called BPCL. Firstly, it used the convolutional neural network to capture the contextual neighborhood information of the target triplet of the subgraph, and linearized the subgraph into a relational path. And it used BERT to initialize edge features. Secondly, it introduced the comparative learning of positive and negative relational paths. Finally, it carried out the relationship prediction by combining contrast learning and supervised training. This paper verifies the improved prediction accuracy of the model on a common benchmark dataset applicable to inductive inference methods.

Foundation Support

广西重点研发计划资助项目(桂科AB22035033)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0253
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 1
Section: Algorithm Research & Explore
Pages: 47-51,56
Serial Number: 1001-3695(2023)01-007-0047-05

Publish History

[2022-08-29] Accepted Paper
[2023-01-05] Printed Article

Cite This Article

尹熹, 梁京章. 基于BERT和路径对比学习的归纳关系预测 [J]. 计算机应用研究, 2023, 40 (1): 47-51,56. (Yin Xi, Liang Jingzhang. Prediction of inductive relationship based on BERT and path contrast learning [J]. Application Research of Computers, 2023, 40 (1): 47-51,56. )

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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