Spatial clustering applied to health area


Autoria(s): Valêncio, Carlos Roberto; De Medeiros, Camila Alves; Ichiba, Fernando Tochio; De Souza, Rogéria Cristiane Gratão
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/12/2011

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.

Formato

427-432

Identificador

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

Idioma(s)

eng

Relação

Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings

Direitos

closedAccess

Palavras-Chave #Database #Geographic information system #Spatial clustering #Spatial data mining #Work accidents #Geographic information #Distributed computer systems #Hardware #Geographic information systems
Tipo

info:eu-repo/semantics/conferencePaper