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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 10

Multimodal named entity recognition method based on multi-granularity progressive fusion

Ying Xujiana
Zhu Yanhuib
Chen Haob
Man Fangtenga
Zhang Zhixuanb
a. College of Computer Science, b. College of Rail Transportation, Hunan University of Technology, Zhuzhou Hunan 412007, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0071

Abstract

To address the lack of fine-grained semantics and inconsistent multimodal representations in existing multimodal named entity recognition methods, this paper proposes a multi-granularity progressive fusion approach for multimodal named entity recognition. First, the proposed framework incorporates a dynamic gated filtering mechanism to selectively extract visual region features relevant to textual semantics via cross-modal dynamic weighting. Additionally, the framework integrates cross-modal alignment and adversarial perturbation mechanisms to strengthen consistency and generalization between textual features and global visual representations. Second, a multi-level progressive fusion network is designed to construct a noise-suppressed and semantically enhanced multi-granularity representation learning system. This architecture hierarchically integrates text-level, text-region image-level, and text-global image-level features through a parallel multi-stage fusion strategy, effectively combining hierarchical feature vectors across different granularities. Extensive experiments conducted on the Twitter-2015 and Twitter-2017 benchmark datasets demonstrate that the proposed method achieves average F1 score improvements of 0.89% and 1.08%, respectively, compared with other multimodal named entity recognition approaches, which confirms the model's effectiveness in named entity recognition tasks.

Foundation Support

国家自然科学基金项目(52272347)、湖南省自然科学基金项目(2025JJ70071)、湖南省教育厅重点项目(22A0408)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0071
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 10

Publish History

[2025-06-04] Accepted Paper

Cite This Article

应旭剑, 朱艳辉, 陈豪, 等. 基于多粒度渐进式融合的多模态命名实体识别方法 [J]. 计算机应用研究, 2025, 42 (10). (2025-06-04). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0071. (Ying Xujian, Zhu Yanhui, Chen Hao, et al. Multimodal named entity recognition method based on multi-granularity progressive fusion [J]. Application Research of Computers, 2025, 42 (10). (2025-06-04). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0071. )

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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