3 papers
cs.IR2026
BIPCL: Bilateral Intent-Enhanced Sequential Recommendation via Embedding Perturbation Contrastive Learning
Shanfan Zhang, Yongyi Lin, Yuan Rao
Accurately modeling users' evolving preferences from sequential interactions remains a central challenge in recommender systems. Recent studies emphasize the importance of capturin…
cs.IR2026
Dual-Perspective Disentangled Multi-Intent Alignment for Enhanced Collaborative Filtering
Shanfan Zhang, Yongyi Lin, Yuan Rao +3
Personalized recommendation requires capturing the complex latent intents underlying user-item interactions. Existing structural models, however, often fail to preserve perspective…
cs.SI2024
Efficient Bipartite Graph Embedding Induced by Clustering Constraints
Shanfan Zhang, Yongyi Lin, Yuan Rao +1
Bipartite graph embedding (BGE) maps nodes to compressed embedding vectors that can reflect the hidden topological features of the network, and learning high-quality BGE is crucial…