• DocumentCode
    3645084
  • Title

    Spatial Clustering Applied to Health Area

  • Author

    Carlos Roberto Valêncio;Fernando Tochio Ichiba;Camila Alves de Medeiros;Rogeria Cristiane Gratao de Souza

  • Author_Institution
    Depto. de Cienc. de Comput. e Estatistica, Univ. Estadual Paulista - Unesp, Sao Jose do Rio Preto, Brazil
  • fYear
    2011
  • Firstpage
    427
  • Lastpage
    432
  • Abstract
    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.
  • Keywords
    "Accidents","Clustering algorithms","Spatial databases","Data mining","Registers","Cities and towns","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2011 12th International Conference on
  • Print_ISBN
    978-1-4577-1807-6
  • Type

    conf

  • DOI
    10.1109/PDCAT.2011.76
  • Filename
    6118544