Searching for modules of networks in the auto-encoder frame
L. Angelini, Daniele Marinazzo, M. Pellicoro, Sebastiano Stramaglia, Stefano Boccaletti, Sumiyoshi Abe, Hans Jürgen Herrmann, P. Quarati, Andrea Rapisarda, Constantino Tsallis · AIP conference proceedings · 2007
We introduce a novel method for identifying the modular structures of a network: this problem is described as a process of compression of information, by means of the autoencoder frame. As a result, the best partition in modules is found to be the maximizer of an objective function: the ratio association. The performance of the proposed method is shown on a real data set and on simulated networks. The optimization algorithm we use is based on the deterministic annealing scheme.