Meanings of supergraph in English

Network features were computed for each subgraph, generating a machine-learning model.

This approach is applied here to generalize the subgraph centrality of nodes in complex networks.

We present an efficient constrained subgraph mining algorithm to discover structure motifs in this setting.

We illustrate the similarities and differences between the generalized subgraph centrality indices as well as among them and some classical centrality measures.

We here present a method of clearly identifying multipartite subgraphs in a network.