Computing the barycenter graph by means of the graph edit distance

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dc.contributor	Institut de Robòtica i Informàtica Industrial
dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor	Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
dc.contributor.author	Bardaji Goikoetxea, Itziar
dc.contributor.author	Ferrer Sumsi, Miquel
dc.contributor.author	Sanfeliu Cortés, Alberto
dc.date	2010
dc.identifier.citation	Bardaji, I.; Ferrer, M.; Sanfeliu, A. Computing the barycenter graph by means of the graph edit distance. A: International Conference on Pattern Recognition. "20th International Conference on Pattern Recognition". 2010, p. 962-965.
dc.identifier.citation	10.1109/ICPR.2010.241
dc.identifier.uri	http://hdl.handle.net/2117/12362
dc.language.iso	eng
dc.relation	http://dx.doi.org/10.1109/ICPR.2010.241
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
dc.subject	Pattern recognition systems
dc.subject	pattern recognition
dc.subject	graph theory
dc.subject	attributed graphs
dc.subject	barycenter graph
dc.subject	graph edit distance
dc.subject	computational geometry
dc.subject	Reconeixement de formes (Informàtica)
dc.subject	Imatges -- Processament
dc.subject	Classificació INSPEC::Pattern recognition
dc.title	Computing the barycenter graph by means of the graph edit distance
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	The barycenter graph has been shown as an alternative to obtain the representative of a given set of graphs. In this paper we propose an extension of the original algorithm which makes use of the graph edit distance in conjunction with the weighted mean of a pair of graphs. Our main contribution is that we can apply the method to attributed graphs with any kind of labels in both the nodes and the edges, equipped with a distance function less constrained than in previous approaches. Experiments done on four different datasets support the validity of the method giving good approximations of the barycenter graph.

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