3 papers
cs.IR2026
Behavior-Aware Dual-Channel Preference Learning for Heterogeneous Sequential Recommendation
Jing Xiao, Dongqi Wu, Liwei Pan +3
Heterogeneous sequential recommendation (HSR) aims to learn dynamic behavior dependencies from the diverse behaviors of user-item interactions to facilitate precise sequential reco…
cs.IR2025
Self-Supervised Representation Learning with ID-Content Modality Alignment for Sequential Recommendation
Donglin Zhou, Weike Pan, Zhong Ming
Sequential recommendation (SR) models often capture user preferences based on the historically interacted item IDs, which usually obtain sub-optimal performance when the interactio…
cs.IR2024
Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation
Guowei Wu, Weike Pan, Qiang Yang +1
Graph neural network (GNN) has emerged as a state-of-the-art solution for item recommendation. However, existing GNN-based recommendation methods rely on a centralized storage of f…