1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,G...1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing operations.Consequently,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62172174,61932004).
文摘1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing operations.Consequently,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.
