Мы используем Cookies Этот веб-сайт использует cookie-файлы, чтобы предлагать вам наиболее актуальную информацию. Просматривая этот веб-сайт, Вы принимаете cookie-файлы.
Network features were computed for each subgraph, generating a machine-learning model.
2
This approach is applied here to generalize the subgraph centrality of nodes in complex networks.
3
We present an efficient constrained subgraph mining algorithm to discover structure motifs in this setting.
4
We illustrate the similarities and differences between the generalized subgraph centrality indices as well as among them and some classical centrality measures.
5
We here present a method of clearly identifying multipartite subgraphs in a network.