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arXiv · 2107.01994

Template-Based Graph Clustering

Mateus Riva·Florian Yger·Pietro Gori·Roberto M. Cesar Jr.·Isabelle Bloch
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Abstract

We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities). The problem is formulated as the matching of a graph to a template with smaller dimension, hence matching $n$ vertices of the observed graph (to be clustered) to the $k$ vertices of a template graph, using its edges as support information, and relaxed on the set of orthonormal matrices in order to find a $k$ dimensional embedding. With relevant priors that encode the density of the clusters and their relationships, our method outperforms classical methods, especially for challenging cases.

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BibTeXRIS

Mateus Riva, Florian Yger, Pietro Gori, Roberto M. Cesar Jr., Isabelle Bloch. 2021-07-05. Template-Based Graph Clustering. https://arxiv.org/abs/2107.01994

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