Personalized and Multi-View Representation for Federated Cold-Start Recommendation

2026-08-27

AI Summary

本文针对联邦冷启动推荐问题，提出PMFRec方法，通过个性化表示生成器和全局多视图编码器解决现有方法的局限性，提高推荐效果和通信效率。

Abstract

Federated recommendation (FedRec) enables personalized modeling without centralizing users' interaction histories, but most existing methods assume a fixed item pool and thus overlook the practical cold-item setting where new items continuously arrive. Under the dual-sided constraint, where the server cannot access clients' interactions while clients cannot access the server's proprietary item attribute features, prior federated cold-start recommendation approaches suffer from three structural limitations: a lack of personalization, compositionality failure caused by forcing heterogeneous semantics into a single embedding space, and training- and communication-inefficiency arising from explicit alignment between separate collaborative and attribute representations. To address these challenges, we propose Personalized and Multi-view Representation for Federated Cold-Start Recommendation (PMFRec). PMFRec learns a personalized representation generator to produce user-specific item representations from attribute features, and introduces a global multi-view encoder with item-adaptive gating and an orthogonality objective to capture complementary semantic views while reducing cross-view redundancy. In addition, PMFRec fuses collaborative and attribute knowledge into a single exchanged item representation, eliminating the need for an explicit client-side regularizer and reducing communication overhead. Extensive experiments on real-world datasets show that PMFRec consistently outperforms strong baselines in cold-item recommendation and further improves user-level fairness, warm-scenario adaptability, and robustness under Local Differential Privacy (LDP).

Problem

• Federated Recommendation
• Cold-Start
• Personalization
• Communication Efficiency
• Semantic Embedding

Innovation

• personalized representation generator
• global multi-view encoder
• item-adaptive gating
• orthogonality objective
• fused item representation