App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 6

Neighborhood information aggregation entity alignment method based on double layer graph attention network

Wang Jianlin
Zhang Hao
Zhang Yongshuang
Ma Chaowei
Qi Ke
Zhang Xiao’ai
Henan Agricultural University, College of Information & Management Sciences(College of Software), Zhengzhou 450046, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0520

Abstract

This paper proposed a method, TGAEA, which combines neighborhood information aggregation with two layers of graph attention networks to tackle challenges in entity alignment tasks within knowledge graphs. Initially, the method utilized the first-layer graph neural network to calculate attention coefficients for entity attribute embedding vectors, aiming to mitigate the impact of irrelevant attributes on entity alignment outcomes. Based on the attribute embedding, the second-layer graph neural network was employed to weight the embedding vectors of entity names, relationships, and structural information, thereby distinguishing the importance of various information within the entity's neighborhood. Additionally, the bootstrap method was utilized to iteratively expand the seed entity pair, and the entity distance measurement was completed by combining the neighborhood information similarity matrix. The experimental results show that the TGAEA model is significantly superior to the current advanced baseline model in the DWY100K dataset, compared to the best method, Hit@1 Hit@10 and MRR indicators increased by 4.18%, 4.81%, and 5%. These findings emphasize the substantial impact of the two-layer graph attention network on aggregating neighborhood information for entity alignment.

Foundation Support

河南省重大科技专项资助项目(171100110600-01)
河南省重点研发与推广专项(科技攻关)资助项目(222102110234)
河南农业大学本科教育教学改革研究与实践项目(2023XJGLX045)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0520
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 6

Publish History

[2024-01-16] Accepted Paper

Cite This Article

王键霖, 张浩, 张永爽, 等. 基于双层图注意力网络的邻域信息聚合实体对齐方法 [J]. 计算机应用研究, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0520. (Wang Jianlin, Zhang Hao, Zhang Yongshuang, et al. Neighborhood information aggregation entity alignment method based on double layer graph attention network [J]. Application Research of Computers, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.10.0520. )

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  • Application Research of Computers Monthly Journal
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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.

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