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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72863
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dc.contributor.authorValêncio, Carlos Roberto-
dc.contributor.authorDe Medeiros, Camila Alves-
dc.contributor.authorIchiba, Fernando Tochio-
dc.contributor.authorDe Souza, Rogéria Cristiane Gratão-
dc.date.accessioned2014-05-27T11:26:14Z-
dc.date.accessioned2016-10-25T18:35:53Z-
dc.date.available2014-05-27T11:26:14Z-
dc.date.available2016-10-25T18:35:53Z-
dc.date.issued2011-12-01-
dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2011.76-
dc.identifier.citationParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 427-432.-
dc.identifier.urihttp://hdl.handle.net/11449/72863-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72863-
dc.description.abstractThe significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.en
dc.format.extent427-432-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectDatabase-
dc.subjectGeographic information system-
dc.subjectSpatial clustering-
dc.subjectSpatial data mining-
dc.subjectWork accidents-
dc.subjectGeographic information-
dc.subjectDistributed computer systems-
dc.subjectHardware-
dc.subjectGeographic information systems-
dc.titleSpatial clustering applied to health areaen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio Preto-
dc.description.affiliationUnespDepto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio Preto-
dc.identifier.doi10.1109/PDCAT.2011.76-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings-
dc.identifier.scopus2-s2.0-84856635878-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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