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Template-Based Graph Clustering

Riva, M.; Yger, Florian; Gori, P.; Cesar, R.; Bloch, I. (2020), Template-Based Graph Clustering, ECML-PKDD, Workshop on Graph Embedding and Minin (GEM), 2020-09, Ghent, BELGIUM

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Type
Communication / Conférence
Date
2020
Titre du colloque
ECML-PKDD, Workshop on Graph Embedding and Minin (GEM)
Date du colloque
2020-09
Ville du colloque
Ghent
Pays du colloque
BELGIUM
Métadonnées
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Auteur(s)
Riva, M. cc
Yger, Florian cc
Gori, P.
Cesar, R.
Bloch, I.
Résumé (EN)
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.
Mots-clés
graph clustering; graph matching; graph segmentation; structural prior