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Título:
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Network clustering by graph coloring: An application to astronomical images
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Autores:
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Zarrazola, E. ;
Montero, Javier ;
Yáñez, Javier ;
Gómez de Castro, Ana Inés
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Tipo de documento:
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texto impreso
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Editorial:
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IEEE, 2011
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/restrictedAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Investigación operativa
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Tipo = Sección de libro
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Resumen:
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In this paper we propose an efficient and polynomial hierarchical clustering technique for unsupervised classification of items being connected by a graph. The output of this algorithm shows the cluster evolution in a divisive way, in such a way that s soon as two items are included in the same cluster they will join a common cluster until the last iteration, in which all the items belong to a singleton cluster. This output can be viewed as a fuzzy clustering in which for each alpha cut we have a standard cluster of the network. The clustering tool we present in this paper allows a hierarchical clustering of related items avoiding some unrealistic constraints that are quite often assumed in clustering problems. The proposed procedure is applied to a hierarchical segmentation problem in astronomical images.
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En línea:
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https://eprints.ucm.es/id/eprint/28655/1/Montero110.pdf
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