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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
772-778

Knowledge graph completion method for disentangled neighborhood information aggregation

Ma Haokai
Qi Yunsong
Wu Yubin
School of Computer, Jiangsu University of Science & Technology, Zhenjiang Jiangsu 212000, China
DOI: 10.19734/j.issn.1001-3695.2023.07.0294

Abstract

Addressing the shortcomings of existing knowledge completion models based on graph neural networks in handling the heterogeneity of knowledge graphs and the limitations posed by most models' adoption of a single static entity representation, this paper introduced a model based on the graph attention mechanism for disentangled neighborhood information aggregation. Initially, this paper learnt the disentangled representation of each entity, providing a multi-component representation for the latent influential factors of entities. Using the attention mechanism, the model selected the most influential latent factors as connection elements for two connected entities. Subsequently, by leveraging a relation-aware attention mechanism, the model adaptively aggregated neighborhood messages at the entity factor level, effectively reducing interference from irrelevant information during aggregation and significantly enhancing the model's semantic representation capability. Moreover, to focus on the most relevant entity component in the scoring process with a given relation, this paper introduced an adaptive scoring coefficient, enabling the model to perceive the relevance between the given relationship and various entity components adaptively. Experimental results on the WN18RR and FB15K-237 datasets indicate that the proposed model outperforms other advanced baseline models in knowledge graph completion tasks, substantially enhancing the model's expressive power.

Foundation Support

国家自然科学基金项目(62261029)
江苏省高校基金面上项目(13KJB520003)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.07.0294
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Algorithm Research & Explore
Pages: 772-778
Serial Number: 1001-3695(2024)03-018-0772-07

Publish History

[2023-09-06] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

马浩凯, 祁云嵩, 吴宇斌. 解纠缠邻域信息聚合的知识图谱补全方法 [J]. 计算机应用研究, 2024, 41 (3): 772-778. (Ma Haokai, Qi Yunsong, Wu Yubin. Knowledge graph completion method for disentangled neighborhood information aggregation [J]. Application Research of Computers, 2024, 41 (3): 772-778. )

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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