自动化学报2026，Vol.52Issue(4)：805-820,16.DOI:10.16383/j.aas.c240659
非完备模态下的可靠多媒体推荐方法
Reliable Multimedia Recommendation Method With Incomplete Modality Data
摘要
Abstract
With the rapid growth of multi-modal content,multimedia recommendation systems play an important role in data mining.However,existing methods typically assume that items possess complete multi-modal informa-tion,making it difficult to adapt to the issue of missing modalities in real-world scenarios.To address this challenge,this paper proposes a novel framework named S2GRec(sparse hypergraph and modality-specific bipartite graphs for incomplete multimedia recommendation).The framework captures high-order intra-modal similarities via an adapt-ive modality completion mechanism based on sparse hypergraphs to achieve unsupervised missing modality comple-tion.Furthermore,it utilizes modality-specific bipartite graphs to model user preferences from different modal per-spectives,thereby enhancing recommendation performance.Experimental results on multiple public datasets and large-scale industrial datasets demonstrate that S2GRec achieves an average improvement of 4.42%over state-of-the-art methods in terms of Recall,Precision,and NDCG,validating its effectiveness in incomplete multimedia recom-mendation tasks.关键词
推荐系统/超图生成/稀疏优化/图卷积网络/非完备多媒体推荐Key words
recommendation systems/hypergraph generation/sparse optimization/graph convolutional network/in-complete multimedia recommendation引用本文复制引用
檀彦超,沈春旭,陈佳敏,马国芳,林政鸿,王石平,易玲玲..非完备模态下的可靠多媒体推荐方法[J].自动化学报,2026,52(4):805-820,16.基金项目
国家自然科学基金(62302098),福建省人工智能产业发展技术项目(2025H0042),福建省自然科学基金(2025J01540),浙江省自然科学基金(LQ23F020007),浙江省"三农九方"科技协作项目(2024SNJF044),浙江省属高校基本科研业务费专项(FR25008Q)资助 Supported by National Natural Science Foundation of China(62302098),Fujian Provincial Artificial Intelligence Industry De-velopment Technology Project(2025H0042),Fujian Provincial Natural Science Foundation(2025J01540),Zhejiang Provincial Natural Science Foundation(LQ23F020007),Zhejiang Provincial Department of Agriculture and Rural Affairs Project(2024SNJF044),and Fundamental Research Funds for the Provincial Universities of Zhejiang(FR25008Q) （62302098）
