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In recent years, the appearance of graph convolutional networks (GCNs) provides a new idea for graph structure data processing. Because of that, they can learn excellent user and item embedding by using cooperative signals of high‐order neighbors, and the GCNs technique shows great potential in the recommendation. The common problem with the bulk of GCN‐based models is that it appears the situation...