舰船电子工程2025，Vol.45Issue(3)：126-132,7.DOI:10.3969/j.issn.1672-9730.2025.03.026
基于多模态知识图谱的服装推荐算法
Multi-modal Clothing Recommendation Algorithm Based on Knowledge Graph
摘要
Abstract
The existing clothing recommendation algorithms have problems with weak interpretability of models and incom-plete aggregation of user information.This article presents a novel clothing recommendation model called the multi-modal dual poli-cy knowledge graph(MDPKT),which enhances interpretability and aggregates user information more effectively.The MDPKT mod-el integrates multi-modal data—textual information like brand and clothing attributes,and visual data from clothing images—into a unified knowledge graph.It employs an improved KGAT model and a ResNet50 pre-training model to process textual and visual da-ta,respectively.A key feature the paper introduced in is the dual aggregation optimization strategy,which optimally selects the num-ber of aggregation hops for both users and items,improving information flow and model accuracy.The model is experimented on the IQON10 dataset and the IQON3000 dataset.The results show that this model can achieve better performance compared with other benchmark models.The improvement effect of the model proposed in this paper on the IQON10 dataset is more obvious.Compared with the SOTA model,MDPKT has significant improvements of 5.99%,5.12%,and 5.01%in AUC,Recall@20,and NDCG@20 re-spectively.On the IQON3000 dataset,these indicators have increased by 4.71%,8.1%,and 4.21%respectively.关键词
服装推荐算法/多模态/知识图谱/双聚合策略Key words
fashion recommendation/multi-model/knowledge graph/dual aggregation policy分类
信息技术与安全科学引用本文复制引用
万晓慧,李维乾,贺妮,邓玉琼..基于多模态知识图谱的服装推荐算法[J].舰船电子工程,2025,45(3):126-132,7.基金项目
教育部重点实验室开放基金项目(编号:NS202118901)资助. （编号:NS202118901）
