Copertina

Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Li, Wang, Shoujin, Zhang, Quangui, Wu, Qiang, Xu, Min
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain Recommendation
di: Wang, Li, et al.
Pubblicazione: (2024)

Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation
di: Guo, Lei, et al.
Pubblicazione: (2026)

Privacy-Preserving Cross-Domain Sequential Recommendation
di: Lin, Zhaohao, et al.
Pubblicazione: (2024)

Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation
di: Huang, Chengkai, et al.
Pubblicazione: (2024)

Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation
di: Wu, Guowei, et al.
Pubblicazione: (2024)

Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference
di: Du, Jing, et al.
Pubblicazione: (2024)

Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation
di: Li, Xiaodong, et al.
Pubblicazione: (2025)

Multi-Domain Recommendation to Attract Users via Domain Preference Modeling
di: Ju, Hyunjun, et al.
Pubblicazione: (2024)

Privacy-Preserving Sequential Recommendation with Collaborative Confusion
di: Wang, Wei, et al.
Pubblicazione: (2024)

FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation
di: Han, Mingzhe, et al.
Pubblicazione: (2025)

Cross-Domain Causal Preference Learning for Out-of-Distribution Recommendation
di: Li, Zhuhang, et al.
Pubblicazione: (2024)

Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
di: Li, Xiaodong, et al.
Pubblicazione: (2026)

Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation
di: Lu, Ziang, et al.
Pubblicazione: (2025)

Modeling Temporal Positive and Negative Excitation for Sequential Recommendation
di: Huang, Chengkai, et al.
Pubblicazione: (2024)

Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users
di: Zeng, Guohang, et al.
Pubblicazione: (2024)

Learning Evolving Preferences: A Federated Continual Framework for User-Centric Recommendation
di: Zhang, Chunxu, et al.
Pubblicazione: (2026)

Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
di: Li, Jin, et al.
Pubblicazione: (2026)

Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
di: Li, Jin, et al.
Pubblicazione: (2025)

A Survey on Cross-Domain Sequential Recommendation
di: Chen, Shu, et al.
Pubblicazione: (2024)

DTRec: Learning Dynamic Reasoning Trajectories for Sequential Recommendation
di: Shao, Yifan, et al.
Pubblicazione: (2025)

Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation
di: Xia, Jiafeng, et al.
Pubblicazione: (2024)

Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation
di: Liu, Weiming, et al.
Pubblicazione: (2025)

Modeling Domain and Feedback Transitions for Cross-Domain Sequential Recommendation
di: Zhang, Changshuo, et al.
Pubblicazione: (2024)

Leveraging Multimodal Data and Side Users for Diffusion Cross-Domain Recommendation
di: Zhang, Fan, et al.
Pubblicazione: (2025)

Reason4Rec: Large Language Models for Recommendation with Deliberative User Preference Alignment
di: Fang, Yi, et al.
Pubblicazione: (2025)

FARM: Frequency-Aware Model for Cross-Domain Live-Streaming Recommendation
di: Li, Xiaodong, et al.
Pubblicazione: (2025)

Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation
di: Qu, Liang, et al.
Pubblicazione: (2024)

Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation
di: Li, Hanyu, et al.
Pubblicazione: (2024)

Structural and Disentangled Adaptation of Large Vision Language Models for Multimodal Recommendation
di: Rao, Zhongtao, et al.
Pubblicazione: (2025)

CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
di: Li, Xiaodong, et al.
Pubblicazione: (2024)

Modeling User Preferences as Distributions for Optimal Transport-Based Cross-Domain Recommendation under Non-Overlapping Settings
di: Xiao, Ziyin, et al.
Pubblicazione: (2025)

A Privacy-Preserving Framework with Multi-Modal Data for Cross-Domain Recommendation
di: Wang, Li, et al.
Pubblicazione: (2024)

WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
di: Hou, Min, et al.
Pubblicazione: (2025)

PersonaX: A Recommendation Agent Oriented User Modeling Framework for Long Behavior Sequence
di: Shi, Yunxiao, et al.
Pubblicazione: (2025)

LISRec: Modeling User Preferences with Learned Item Shortcuts for Sequential Recommendation
di: Xin, Haidong, et al.
Pubblicazione: (2025)

Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation
di: Liu, Yu, et al.
Pubblicazione: (2025)

FeDecider: An LLM-Based Framework for Federated Cross-Domain Recommendation
di: He, Xinrui, et al.
Pubblicazione: (2026)

MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendation
di: Wu, Ziqing, et al.
Pubblicazione: (2024)

Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach
di: Zhang, Chunxu, et al.
Pubblicazione: (2024)

PDSR: A Privacy-Preserving Diversified Service Recommendation Method on Distributed Data
di: Wang, Lina, et al.
Pubblicazione: (2024)