Spatial clustering applied to health area

Detalhes bibliográficos
Autor(a) principal: Valêncio, Carlos Roberto [UNESP]
Data de Publicação: 2011
Outros Autores: De Medeiros, Camila Alves [UNESP], Ichiba, Fernando Tochio [UNESP], De Souza, Rogéria Cristiane Gratão [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/PDCAT.2011.76
http://hdl.handle.net/11449/72863
Resumo: The 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.
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spelling Spatial clustering applied to health areaDatabaseGeographic information systemSpatial clusteringSpatial data miningWork accidentsGeographic informationDistributed computer systemsHardwareGeographic information systemsThe 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.Depto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio PretoDepto. de Ciências de Computação e Estatística Universidade Estadual Paulista - Unesp, São José do Rio PretoUniversidade Estadual Paulista (Unesp)Valêncio, Carlos Roberto [UNESP]De Medeiros, Camila Alves [UNESP]Ichiba, Fernando Tochio [UNESP]De Souza, Rogéria Cristiane Gratão [UNESP]2014-05-27T11:26:14Z2014-05-27T11:26:14Z2011-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject427-432http://dx.doi.org/10.1109/PDCAT.2011.76Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 427-432.http://hdl.handle.net/11449/7286310.1109/PDCAT.2011.762-s2.0-84856635878464481225387583259146517545178640000-0002-9325-31590000-0002-7449-9022Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedingsinfo:eu-repo/semantics/openAccess2021-10-23T10:02:43Zoai:repositorio.unesp.br:11449/72863Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:31:08.770241Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Spatial clustering applied to health area
title Spatial clustering applied to health area
spellingShingle Spatial clustering applied to health area
Valêncio, Carlos Roberto [UNESP]
Database
Geographic information system
Spatial clustering
Spatial data mining
Work accidents
Geographic information
Distributed computer systems
Hardware
Geographic information systems
title_short Spatial clustering applied to health area
title_full Spatial clustering applied to health area
title_fullStr Spatial clustering applied to health area
title_full_unstemmed Spatial clustering applied to health area
title_sort Spatial clustering applied to health area
author Valêncio, Carlos Roberto [UNESP]
author_facet Valêncio, Carlos Roberto [UNESP]
De Medeiros, Camila Alves [UNESP]
Ichiba, Fernando Tochio [UNESP]
De Souza, Rogéria Cristiane Gratão [UNESP]
author_role author
author2 De Medeiros, Camila Alves [UNESP]
Ichiba, Fernando Tochio [UNESP]
De Souza, Rogéria Cristiane Gratão [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Valêncio, Carlos Roberto [UNESP]
De Medeiros, Camila Alves [UNESP]
Ichiba, Fernando Tochio [UNESP]
De Souza, Rogéria Cristiane Gratão [UNESP]
dc.subject.por.fl_str_mv Database
Geographic information system
Spatial clustering
Spatial data mining
Work accidents
Geographic information
Distributed computer systems
Hardware
Geographic information systems
topic Database
Geographic information system
Spatial clustering
Spatial data mining
Work accidents
Geographic information
Distributed computer systems
Hardware
Geographic information systems
description The 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.
publishDate 2011
dc.date.none.fl_str_mv 2011-12-01
2014-05-27T11:26:14Z
2014-05-27T11:26:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/PDCAT.2011.76
Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 427-432.
http://hdl.handle.net/11449/72863
10.1109/PDCAT.2011.76
2-s2.0-84856635878
4644812253875832
5914651754517864
0000-0002-9325-3159
0000-0002-7449-9022
url http://dx.doi.org/10.1109/PDCAT.2011.76
http://hdl.handle.net/11449/72863
identifier_str_mv Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 427-432.
10.1109/PDCAT.2011.76
2-s2.0-84856635878
4644812253875832
5914651754517864
0000-0002-9325-3159
0000-0002-7449-9022
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 427-432
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128940516048896

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