Spatial clustering applied to health area
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Data
2011-12-01
Autores
Valêncio, Carlos Roberto [UNESP]
De Medeiros, Camila Alves [UNESP]
Ichiba, Fernando Tochio [UNESP]
De Souza, Rogéria Cristiane Gratão [UNESP]
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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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Database, Geographic information system, Spatial clustering, Spatial data mining, Work accidents, Geographic information, Distributed computer systems, Hardware, Geographic information systems
Como citar
Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 427-432.