Hierarchical information clustering by means of topologically embedded graphs.

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and ana...

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Auteurs principaux: Won-Min Song, T Di Matteo, Tomaso Aste
Format: article
Langue:EN
Publié: Public Library of Science (PLoS) 2012
Sujets:
R
Q
Accès en ligne:https://doaj.org/article/a720d768c28243c4980b470a8ac3213a
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