通信学报2026，Vol.47Issue(5)：91-102,12.DOI:10.11959/j.issn.1000-436x.TXXB260048
基于多模态用户图的跨领域服务匹配方法
Cross-domain service matching method based on multimodal user graph
摘要
Abstract
In cross-domain service matching scenarios,user preferences are distributed across multiple service domains and exhibit pronounc multimodal and heterogeneous characteristics.Accurately modeling users'cross-domain preferences are therefore crucial for improving matching performance.Existing methods predominantly relied on unified embedding spaces,which tended to compress multi-source preferences and overlooked modality-specific discrepancies.To address these limitations,a multimodal user graph-based cross-domain service matching method was proposed.The proposed ap-proach constructed a multimodal user graph using preference labels as anchors,explicitly modeling user preferences across text,image,audio,and video modalities,while incorporating an open knowledge graph and virtual auxiliary nodes to en-hance graph connectivity.Furthermore,a modality-aware graph pooling module,termed MUGPool,was designed to adap-tively aggregate preferences across different modalities.Experimental results on the Amazon multimodal multi-domain data-set demonstrate that the proposed method outperforms state-of-the-art cross-domain service matching baselines.关键词
跨领域服务匹配/多模态用户图/模态感知图池化/模态聚合Key words
cross-domain service matching/multimodal user graph/modality-aware graph pooling/modality aggregation分类
信息技术与安全科学引用本文复制引用
王海艳,刘万宇,骆健,张少聪..基于多模态用户图的跨领域服务匹配方法[J].通信学报,2026,47(5):91-102,12.基金项目
国家自然科学基金资助项目(No.62272243) The National Natural Science Foundation of China(No.62272243) （No.62272243）
