Repository logo

CHSMST+: An algorithm for spatial clustering

Loading...
Thumbnail Image

Advisor

Coadvisor

Graduate program

Undergraduate course

Journal Title

Journal ISSN

Volume Title

Publisher

Type

Work presented at event

Access right

Acesso abertoAcesso Aberto

Abstract

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 nonspatial data, user interaction is not necessary, and use of multithreading technique to improve the performance. The algorithm was tested ia a real database of health area.

Description

Keywords

CHSMST (Clustering based on Hyper Surface and Minimum Spanning Tree), Hyper Surface Classification (HSC), Minimum Spanning Tree (MST), Spatial Clustering, Spatial Data Mining

Language

English

Citation

Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings, p. 352-357.

Related itens

Sponsors

Units

Departments

Undergraduate courses

Graduate programs

Other forms of access