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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 7
2031-2038

Knowledge graph embedding model for bidirectional graph attention mechanism with hierarchical type information

Zhai Shepinga,b
Li Fangyia
Li Hanga
Yang Ruia
a. School of Computer Science & Technology, b. Shaanxi Key Laboratory of Network Data Analysis & Intelligent Processing, Xi'an University of Posts & Telecommunications, Xi'an 710121, China
DOI: 10.19734/j.issn.1001-3695.2022.12.0763

Abstract

Knowledge graph embedding designs to map the entities and relations into low-dimensional and dense vector spaces. The existing embedded models still have the following two defects: most of the existing models only focus on the semantic information of knowledge graph, but ignore plentiful hidden information of triples; the existing models only concern the unidirectional information of the entity, but ignore the bidirectional potential information. This paper proposed the knowledge graph embedding model Bi-HTGAT to solve these problems. The model designed a hierarchical type attention mechanism, considered the contribution of different entities of each type to the central entity under different relations. At the same time, this paper introduced the directional attention mechanism of the relations, fused the neighbor information in different directions to update the entities and relations embedding, and finally aggregated the two parts of information to obtain the final embedding of the entity. The experimental results show that Bi-HTGAT performs better than other baseline models in link prediction, which fully proves that Bi-HTGAT can further improve the accuracy of embedding results.

Foundation Support

国家自然科学基金资助项目(61373116)
工业和信息化部通信软科学项目(2018-R-26)
陕西省教育厅科学研究计划项目(18JK0697)
陕西省社会科学基金资助项目(2016N008)
陕西省重点研发计划项目(2022GY-038)
西安市社会科学规划基金资助项目(17X63)
西安邮电大学研究生创新基金资助项目(CXJJYL2021044)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.12.0763
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 7
Section: Algorithm Research & Explore
Pages: 2031-2038
Serial Number: 1001-3695(2023)07-017-2031-08

Publish History

[2023-02-15] Accepted Paper
[2023-07-05] Printed Article

Cite This Article

翟社平, 李方怡, 李航, 等. 融合层次类型信息的双向图注意力机制的知识图谱嵌入模型 [J]. 计算机应用研究, 2023, 40 (7): 2031-2038. (Zhai Sheping, Li Fangyi, Li Hang, et al. Knowledge graph embedding model for bidirectional graph attention mechanism with hierarchical type information [J]. Application Research of Computers, 2023, 40 (7): 2031-2038. )

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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