MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering. (arXiv:2204.02338v1 [cs.SI])

Collaborative filtering (CF) is widely used by personalized recommendation
systems, which aims to predict the preference of users with historical
user-item interactions. In recent years, Graph Neural Networks (GNNs) have been
utilized to build CF models and have shown promising performance. Recent
state-of-the-art GNN-based CF approaches simply attribute their performance
improvement to the high-order neighbor aggregation ability of GNNs. However, we
observe that some powerful deep GNNs such as JKNet and DropEdge, can
effectively exploit high-order neighbor information on other …

arxiv collaborative collaborative filtering distance learning graph learning markov