山西大学学报（自然科学版）2026，Vol.49Issue(3)：377-386,10.DOI:10.13451/j.sxu.ns.2025117
基于跨域元学习的用户冷启动推荐算法
Cold-start Recommendation Algorithm Based on Cross-domain Meta-learning
摘要
Abstract
To address two issues in existing mapping-based cross-domain recommendation algorithms—namely,the neglect of target domain contextual information during interest transfer and the model's high sensitivity to the scale of overlapping users—a novel end-to-end optimized Cross-domain Meta-learning Driven Interest Transfer Network(CMITN)is proposed.CMITN introduces a cross-domain attention mechanism that is sensitive to the target domain,which reconstructs the source domain's interest represen-taion based on candidate item characteristics.A convolutional meta-learning network is designed to dynamically generate personal-ized mapping functions,alleviating data sparsity dependence.A dual-objective joint optimization paradigm is constructed to opti-mize both the recommendation task and the representation alignment,ensuring a consistent mapping of the full interest space.Five cross-domain recommendation tasks were constructed using Amazon and Hello datasets,followed by extensive experiments.The ex-perimental results show that the proposed algorithm outperforms other baseline models in both AUC(Area Under Curve)and Recall.In the business scenario of Hello Life Services,the algorithm led to a 4.5%increase in CTR(Click Through Rate)and a 7.0%im-provement in GMV(Gross Merchandise Volume)per user for new users.关键词
跨域推荐/注意力机制/哈啰租车/生活服务Key words
cross-domain recommendation/attention mechanism/hello rent car/life services分类
信息技术与安全科学引用本文复制引用
吴鑫卓,侯亚伟,贾立,许侃,林原,林鸿飞..基于跨域元学习的用户冷启动推荐算法[J].山西大学学报（自然科学版）,2026,49(3):377-386,10.基金项目
国家自然科学基金(61976036) （61976036）
中国工程院重大咨询研究项目子课题(2023-JB-10-04) （2023-JB-10-04）
