App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 6

Expert-driven multi-information domain collaborative multimodal sentiment analysis

Feng Guanga
Lin Yibaob
Liu Xintinga
Sun Xianglib
Huang Junhuib
Liao Beirongb
Zhou Kedonga
a. School of Automation, b. School of Computer Science, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0435

Abstract

To address the limitations in Multimodal Sentiment Analysis (MSA) , specifically the insufficient capture of heterogeneous modality correlations and inadequate collaborative modeling of shared-private spaces, this paper proposes a multi-information domain collaborative framework driven by a Mixture-of-Experts (MoE) model. Specifically, the framework utilizes a sparse MoE module to distill cross-modal shared representations and generate dynamic sharpness factors, which regulate the fusion process of a dual-stage sharpness-coordinated attention mechanism. Furthermore, this paper designs a Semantic Complementary Gating (SCG) mechanism that injects the orthogonal components of MoE shared vectors into attention outputs via confidence-based gating, thereby achieving semantic completion and redundancy suppression for private representations. Experimental results on the CMU-MOSI and CMU-MOSEI datasets demonstrate that the proposed method outperforms existing state-of-the-art baselines in both sentiment classification and intensity regression tasks. The results verify the framework's effectiveness in enhancing the accuracy and robustness of sentiment recognition by stably modeling cross-modal complementarity and multi-information domain collaboration.

Foundation Support

国家自然科学基金重点项目(62237001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0435
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 6

Publish History

[2026-02-26] Accepted Paper

Cite This Article

冯广, 林忆宝, 刘馨婷, 等. 基于专家模型驱动多信息域协同的多模态情感分析 [J]. 计算机应用研究, 2026, 43 (6). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0435. (Feng Guang, Lin Yibao, Liu Xinting, et al. Expert-driven multi-information domain collaborative multimodal sentiment analysis [J]. Application Research of Computers, 2026, 43 (6). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0435. )

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  • Application Research of Computers Monthly Journal
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    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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