Abstract
Large networks call for approaches which allow to represent their relevant properties. One relevant approach can consider the decomposition of the defined networks in significant subgraphs as k-cores. So it is possible to identify the nodes which can have an important role on the network. In particular they can provide a specific connection between the different subgraphs and with nodes showing a higher centrality. It is also possible to represent the core-periphery structure. Interval regression offers the possibility to represent the relationship between the structural characteristics of the different nodes with same k-coreness. The combined different approaches of interval regression in order to take into account our analysis of center, upper and lower bounds allow to discover the relevant structure of the network.
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