App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

Dual-stream heterogeneous information fusion model for entity alignment

He Xinyu
Li Yan
Song Haojun
College of Medical Information Engineering, Gansu University of Traditional Chinese Medicine, Lanzhou Ganshu 730101, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0038

Abstract

Addressing the structural heterogeneity and attribute semantic bias across different knowledge graphs, which are major bottlenecks in entity alignment, this paper proposes a Dual-stream Heterogeneous Information Fusion Model for Entity Alignment (DHIF) . The model employs a dual-channel decoupled design for structure and attribute sides. On the structure side, it captures the structural and relational patterns of target graphs explicitly via intra-graph relation-aware aggregation and cross-graph multi-path differentiated cross-attention. On the attribute side, it calibrates cross-graph shifts in attribute semantics via attention-weighted aggregation and independent cross-graph learning. The outputs from both sides are adaptively fused via Bayesian optimization, followed by a deferred acceptance algorithm to achieve one-to-one global matching. Experimental results on three cross-lingual datasets of DBP15K (Chinese-English, Japanese-English, and French-English) show that DHIF achieves Hits@1 scores of 92.5%, 94.2%, and 98.2%, respectively, all outperforming existing baseline models. These results validate the effectiveness of the dual-stream cross-graph interaction design in mitigating graph heterogeneity and improving alignment performance.

Foundation Support

中国高校产学研创新基金一蓝点分布式智能计算项目(2021LDA09002)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0038
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-07-08] Accepted Paper

Cite This Article

何欣宇, 李燕, 宋豪俊. 基于双流异质信息的实体对齐模型 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0038. (He Xinyu, Li Yan, Song Haojun. Dual-stream heterogeneous information fusion model for entity alignment [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0038. )

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  • 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.

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