<div><p>We propose a novel method to test the existence of community structure in undirected, real-valued, edge-weighted graphs. The method is based on the asymptotic behavior of extreme eigenvalues of a real symmetric edge-weight matrix. We provide a theoretical foundation for this method and report on its performance using synthetic and real data, suggesting that this new method outperforms other state-of-the-art methods.</p></div
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
Doctor of PhilosophyDepartment of StatisticsMichael HigginsIn many sciences---for example Sociology,...
Many methods have been proposed for community detection in networks. Some of the most promising are ...
We propose a novel method to test the existence of community structure in undirected, real-valued, e...
We propose a novel method to test the existence of community structure in undirected, real-valued, e...
Abstract Community detection is a fundamental procedure in the analysis of network data. Despite dec...
Community structure is one of the main structural features of networks, revealing both their interna...
Networks can take on many different forms, such as the people from the University you attend. Withi...
The classical setting of community detection consists of networks exhibiting a clustered structure. ...
Community structure is one of the main structural features of networks, revealing both their interna...
International audienceCommunities are an important type of structure in networks. Graph filters, suc...
We analyze the spectral properties of complex networks focusing on their relation to the community s...
International audienceWe formalize the problem of detecting a community in a network into testing wh...
A common and important problem arising in the study of net-works is how to divide the vertices of a ...
Abstract—We present a new evolutionary algorithm for com-munity structure detection in both undirect...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
Doctor of PhilosophyDepartment of StatisticsMichael HigginsIn many sciences---for example Sociology,...
Many methods have been proposed for community detection in networks. Some of the most promising are ...
We propose a novel method to test the existence of community structure in undirected, real-valued, e...
We propose a novel method to test the existence of community structure in undirected, real-valued, e...
Abstract Community detection is a fundamental procedure in the analysis of network data. Despite dec...
Community structure is one of the main structural features of networks, revealing both their interna...
Networks can take on many different forms, such as the people from the University you attend. Withi...
The classical setting of community detection consists of networks exhibiting a clustered structure. ...
Community structure is one of the main structural features of networks, revealing both their interna...
International audienceCommunities are an important type of structure in networks. Graph filters, suc...
We analyze the spectral properties of complex networks focusing on their relation to the community s...
International audienceWe formalize the problem of detecting a community in a network into testing wh...
A common and important problem arising in the study of net-works is how to divide the vertices of a ...
Abstract—We present a new evolutionary algorithm for com-munity structure detection in both undirect...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
Doctor of PhilosophyDepartment of StatisticsMichael HigginsIn many sciences---for example Sociology,...
Many methods have been proposed for community detection in networks. Some of the most promising are ...