169 citations · 203 across the 3 of their papers we have counts for
4 papers
A Review-aware Graph Contrastive Learning Framework for Recommendation
Jie Shuai, Kun Zhang, Le Wu +4
Most modern recommender systems predict users preferences with two components: user and item embedding learning, followed by the user-item interaction modeling. By utilizing the au…
ProFairRec: Provider Fairness-aware News Recommendation
Tao Qi, Fangzhao Wu, Chuhan Wu +5
News recommendation aims to help online news platform users find their preferred news articles. Existing news recommendation methods usually learn models from historical user behav…
DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
Le Wu, Junwei Li, Peijie Sun +3
Social recommendation has emerged to leverage social connections among users for predicting users' unknown preferences, which could alleviate the data sparsity issue in collaborati…
A Neural Influence Diffusion Model for Social Recommendation
Le Wu, Peijie Sun, Yanjie Fu +3
Precise user and item embedding learning is the key to building a successful recommender system. Traditionally, Collaborative Filtering(CF) provides a way to learn user and item em…