Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
Most of the faster community extraction algorithms are based on the Clauset, Newman and Moore (CNM), which is employed for networks with sizes up to 500,000 nodes. The modificatio...
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
— A deep understanding of the structural properties of wireless networks is critical for evaluating the performance of network protocols and improving their designs. Many protoco...
Jianer Chen, Anxiao Jiang, Iyad A. Kanj, Ge Xia, F...