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Statistical test for detecting community structure in real-valued edge-weighted graphs.


ABSTRACT: 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.

SUBMITTER: Tokuda T 

PROVIDER: S-EPMC5860707 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Statistical test for detecting community structure in real-valued edge-weighted graphs.

Tokuda Tomoki T  

PloS one 20180320 3


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. ...[more]

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