A density-based spatial clustering for physical constraints |
| |
Authors: | Xin Wang Camilo Rostoker Howard J Hamilton |
| |
Affiliation: | (1) Department of Geomatics Engineering, University of Calgary, Calgary, AB, T2N 1N4, Canada;(2) Department of Computer Science, University of Regina, Regina, SK, S4S 0A2, Canada |
| |
Abstract: | We propose a spatial clustering method, called DBRS+, which aims to cluster spatial data in the presence of both obstacles
and facilitators. It can handle datasets with intersected obstacles and facilitators. Without preprocessing, DBRS+ processes
constraints during clustering. It can find clusters with arbitrary shapes. DBRS+ has been empirically evaluated using synthetic
and real data sets and its performance has been compared to DBRS and three related methods for handling obstacles, namely
AUTOCLUST+, DBCLuC*, and DBRS_O. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|