Knowledge discovery process for description of spatially referenced clusters

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Spatial clustering is an important field of spatial data mining and knowledge discovery that serves to partition a spatial data set to obtain disjoint subsets with spatial elements that are similar to each other. Existing algorithms can be used to perform three types of cluster analyses, including c...

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Detalles Bibliográficos
Autores principales:	Róttoli, Giovanni, Merlino, Hernán, García Martínez, Ramón
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2017
Materias:	Ciencias Informáticas Decision tree learning Knowledge discovery process Regionalization Spatial clustering Spatial data mining
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/87556
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-87556
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Decision tree learning Knowledge discovery process Regionalization Spatial clustering Spatial data mining
spellingShingle	Ciencias Informáticas Decision tree learning Knowledge discovery process Regionalization Spatial clustering Spatial data mining Róttoli, Giovanni Merlino, Hernán García Martínez, Ramón Knowledge discovery process for description of spatially referenced clusters
topic_facet	Ciencias Informáticas Decision tree learning Knowledge discovery process Regionalization Spatial clustering Spatial data mining
description	Spatial clustering is an important field of spatial data mining and knowledge discovery that serves to partition a spatial data set to obtain disjoint subsets with spatial elements that are similar to each other. Existing algorithms can be used to perform three types of cluster analyses, including clustering of spatial points, regionalization and point pattern analysis. However, all these existing methods do not provide a description of the discovered spatial clusters, which is useful for decision making in many different fields. This work proposes a knowledge discovery process for the description of spatially referenced clusters that uses decision tree learning algorithms. Two proofs of concept of the proposed process using different spatial clustering algorithm on real data are also provided.
format	Objeto de conferencia Objeto de conferencia
author	Róttoli, Giovanni Merlino, Hernán García Martínez, Ramón
author_facet	Róttoli, Giovanni Merlino, Hernán García Martínez, Ramón
author_sort	Róttoli, Giovanni
title	Knowledge discovery process for description of spatially referenced clusters
title_short	Knowledge discovery process for description of spatially referenced clusters
title_full	Knowledge discovery process for description of spatially referenced clusters
title_fullStr	Knowledge discovery process for description of spatially referenced clusters
title_full_unstemmed	Knowledge discovery process for description of spatially referenced clusters
title_sort	knowledge discovery process for description of spatially referenced clusters
publishDate	2017
url	http://sedici.unlp.edu.ar/handle/10915/87556
work_keys_str_mv	AT rottoligiovanni knowledgediscoveryprocessfordescriptionofspatiallyreferencedclusters AT merlinohernan knowledgediscoveryprocessfordescriptionofspatiallyreferencedclusters AT garciamartinezramon knowledgediscoveryprocessfordescriptionofspatiallyreferencedclusters
bdutipo_str	Repositorios
_version_	1764820490191372292

Knowledge discovery process for description of spatially referenced clusters

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