Publicação:
Spatial clustering applied to health area

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dc.contributor.authorValêncio, Carlos Roberto [UNESP]
dc.contributor.authorDe Medeiros, Camila Alves [UNESP]
dc.contributor.authorIchiba, Fernando Tochio [UNESP]
dc.contributor.authorDe Souza, Rogéria Cristiane Gratão [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:26:14Z
dc.date.available2014-05-27T11:26:14Z
dc.date.issued2011-12-01
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.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.format.extent427-432
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.doi10.1109/PDCAT.2011.76
dc.identifier.lattes4644812253875832
dc.identifier.lattes5914651754517864
dc.identifier.orcid0000-0002-9325-3159
dc.identifier.orcid0000-0002-7449-9022
dc.identifier.scopus2-s2.0-84856635878
dc.identifier.urihttp://hdl.handle.net/11449/72863
dc.language.isoeng
dc.relation.ispartofParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings
dc.rights.accessRightsAcesso aberto
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.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dspace.entity.typePublication
unesp.author.lattes4644812253875832[1]
unesp.author.lattes5914651754517864[4]
unesp.author.orcid0000-0002-9325-3159[1]
unesp.author.orcid0000-0002-7449-9022[4]
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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São José do Rio Preto - IBILCE - Instituto de Biociências, Letras e Ciências Exatas