Clustering Communities Using Interval K-Means

On large networks there is a specific need to consider specific patterns which can be related to structured groups of nodes which could be also defined communities. In this sense we will propose an approach to cluster the different communities using interval data. This approach is relevant in the context of the analysis of large network and in particular on discovering the different functionalities of the communities inside a network. The approach is shown in this paper by considering different examples of networks by means of synthetic data. The application of the approach is specifically related to a large network as the co-authorship network in Astrophysics