Computing Graph Similarity via Graph Matching

A computer-implemented method for calculating a similarity between a pair of graph-structured objects by learning-based techniques. The operations include computing the node embeddings of a pair of graph-structured objects of two computer graphs utilizing a hierarchical graph matching network (HGMN). A first component of the HGMN performs graph matching of global-level graph interactions of the two computer graphs. A second component of the HGMN performs graph matching of cross-level node-graph interactions of the two computer graphs. There is an aggregating of features learned from the graph matching of the global-level graph interactions and the cross-level node-graph interactions. At least one of a graph-graph classification or a graph-graph regression is performed utilizing the learned features of the two computer graphs.