CHSMST plus : An Algorithm for Spatial Clustering - Valencio, Carlos Roberto [UNESP]; Medeiros, Camila Alves [UNESP]; Neves, Leandro Alves [UNESP]; Donega Zafalon, Geraldo Francisco [UNESP]; Gratao de Souza, Rogeria Cristiane [UNESP]; Colombini, Angelo Cesar; Shen, H.; Sang, Y.; Tian, H. (Ieee, 2016)
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.
Keywords: Spatial Data Mining; Spatial Clustering; Hyper Surface Classification (HSC); Minimum Spanning Tree (MST); CHSMST (Clustering based on Hyper Surface and Minimum Spanning Tree)