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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 1
100-105

Multi-modal entity alignment model based on adaptive fusion technology

Ren Chulan1,2
Yu Zhenkun1,2
Guan Chao1,2
Jing Lizhi1,2
1. School of Computer Science & Technology, Shenyang University of Chemical Technology, Shenyang 110142, China
2. Liaoning Provincial Key Laboratory of Intelligent Technology for Chemical Process Industry, Shenyang 110142, China
DOI: 10.19734/j.issn.1001-3695.2024.05.0187

Abstract

Multi-modal entity alignment aims to identify equivalent entities between different multi-modal knowledge graphs composed of structured triples and images associated with entities. The existing research on multi-modal entity alignment mainly focuses on multi-modal fusion strategies, ignoring the problems of modal imbalance and difficulty in integrating different modalities, and fails to fully utilize multi-modal information. To solve these problems, this paper proposed the MACEA model, this model used the multi-modal variational autoencoder method to actively complete the missing modal information, the dynamic modal fusion method to integrate and complement the information of different modalities, and the inter-modal contrastive learning method to model the inter-modal relations. These methods effectively solve the problems of modal missing and the difficulty in modal fusion. Compared with the baseline model, MACEA improves the hits@1 and MRR indicators by 5.72% and 6.78%, respectively. The experimental results show that the proposed method can effectively identify aligned entity pairs, with high accuracy and practicality.

Foundation Support

辽宁省教育厅科学研究资助项目(LJKZ0449,LJKZ0434)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.05.0187
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 1
Section: Algorithm Research & Explore
Pages: 100-105
Serial Number: 1001-3695(2025)01-014-0100-06

Publish History

[2025-01-05] Printed Article

Cite This Article

任楚岚, 于振坤, 关超, 等. 基于自适应融合技术的多模态实体对齐模型 [J]. 计算机应用研究, 2025, 42 (1): 100-105. (Ren Chulan, Yu Zhenkun, Guan Chao, et al. Multi-modal entity alignment model based on adaptive fusion technology [J]. Application Research of Computers, 2025, 42 (1): 100-105. )

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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