CHSMST plus : An Algorithm for Spatial Clustering

Actas de congresos

Fecha

2016-01-01

Registro en:

2016 17th International Conference On Parallel And Distributed Computing, Applications And Technologies (pdcat). New York: Ieee, p. 352-357, 2016.

http://hdl.handle.net/11449/165635

10.1109/PDCAT.2016.80

WOS:000403774200071

4644812253875832

2139053814879312

0000-0002-9325-3159

Autor

Universidade Estadual Paulista (Unesp)

Universidade Federal de São Carlos (UFSCar)

Institución

Universidade Estadual Paulista (Brasil)

Resumen

Spatial clustering has been widely studied due to its application in several areas. However, the algorithms of such technique still need to overcome several challenges to achieve satisfactory results on a timely basis. This work presents an algorithm for spatial clustering based on CHSMST, which allows: data clustering considering both distance and similarity, enabling to correlate spatial and non-spatial data; user interaction is not necessary; and use of multithreading technique to improve the performance. The algorithm was tested is a real database of health area.

Materias

Spatial Data Mining

Spatial Clustering

Hyper Surface Classification (HSC)

Minimum Spanning Tree (MST)

CHSMST (Clustering based on Hyper Surface and Minimum Spanning Tree)

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