Identification of network modules by optimization of ratio association

Details Identification of network modules by optimization of ratio association Identification of network modules by optimization of ratio association

2006-10-06

arxiv.org/abs/cond-mat/0610182v2

Physics

Condensed Matter

Disordered Systems and Neural Networks

Scientific paper

10.1063/1.2732162

We introduce a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association. This cost function arises when the communities detection problem is described in the probabilistic autoencoder frame. An analogy with kernel k-means methods allows to develop an efficient optimization algorithm, based on the deterministic annealing scheme. The performance of the proposed method is shown on a real data set and on simulated networks.

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