Fairness-aware recommendation alleviates discrimination issues to build trustworthy recommendation systems. Explaining the causes of unfair recommendations is critical, as it …
Traditional recommenders suffer from hidden confounding factors, leading to the spurious correlations between user/item profiles and user preference prediction, ie, the confounding …
Graph collaborative filtering (GCF) has emerged as a prominent method in recommendation systems, leveraging the power of graph learning to enhance traditional collaborative filtering …