CHSMST+: An algorithm for spatial clustering
Loading...
Files
External sources
External sources
Date
Advisor
Coadvisor
Graduate program
Undergraduate course
Journal Title
Journal ISSN
Volume Title
Publisher
Type
Work presented at event
Access right
Acesso aberto

Files
External sources
External sources
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.





