General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
An Zhang,
Wenchang Ma,
Pengbo Wei
et al.
Abstract:Graph neural networks (GNNs) have shown impressive performance in recommender systems, particularly in collaborative filtering (CF). The key lies in aggregating neighborhood information on a user-item interaction graph to enhance user/item representations. However, we have discovered that this aggregation mechanism comes with a drawback -it amplifies biases present in the interaction graph. For instance, a user's interactions with items can be driven by both unbiased true interest and various biased factors li… Show more
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