A Bayesian Approach to Network Modularity

21 Sep 2007Jake M. HofmanChris H. Wiggins

We present an efficient, principled, and interpretable technique for inferring module assignments and for identifying the optimal number of modules in a given network. We show how several existing methods for finding modules can be described as variant, special, or limiting cases of our work, and how the method overcomes the resolution limit problem, accurately recovering the true number of modules... (read more)

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