4 papers
A Survey on Bundle Recommendation: Methods, Applications, and Challenges
Meng Sun, Lin Li, Ming Li +5
In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by…
AesRec: A Dataset for Aesthetics-Aligned Clothing Outfit Recommendation
Wenxin Ye, Lin Li, Ming Li +3
Clothing recommendation extends beyond merely generating personalized outfits; it serves as a crucial medium for aesthetic guidance. However, existing methods predominantly rely on…
Modeling Item-Level Dynamic Variability with Residual Diffusion for Bundle Recommendation
Dong Zhang, Lin Li, Ming Li +4
Existing solutions for bundle recommendation (BR) have achieved remarkable effectiveness for predicting the user's preference for prebuilt bundles. However, bundle-item (B-I) affil…
Learning to Fast Unrank in Collaborative Filtering Recommendation
Junpeng Zhao, Lin Li, Ming Li +2
Modern data-driven recommendation systems risk memorizing sensitive user behavioral patterns, raising privacy concerns. Existing recommendation unlearning methods, while capable of…