3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.IR2026
Latent Factor Modeling with Expert Network for Multi-Behavior Recommendation
Mingshi Yan, Zhiyong Cheng, Yahong Han +1
Traditional recommendation methods, which typically focus on modeling a single user behavior (e.g., purchase), often face severe data sparsity issues. Multi-behavior recommendation…
cs.IR2025
User Invariant Preference Learning for Multi-Behavior Recommendation
Mingshi Yan, Zhiyong Cheng, Fan Liu +2
In multi-behavior recommendation scenarios, analyzing users' diverse behaviors, such as click, purchase, and rating, enables a more comprehensive understanding of their interests,…
cs.IR2024★ 3 cited
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
Mingshi Yan, Fan Liu, Jing Sun +3
In recommender systems, multi-behavior methods have demonstrated their effectiveness in mitigating issues like data sparsity, a common challenge in traditional single-behavior reco…