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To address these limitations, we propose a hybrid method named CGEDN based on Graph Neural Networks and learnable node matching. Specifically, CGEDN starts with cross-graph feature aggregation layers, ...

Abstract: Graph neural networks (GNNs) are capable of modeling graph data using various types of nodes and edges, and thus can be widely used in the fields of recommender systems and bioinformatics.