Constrained clustering objects on a spatial network

Abstract

Clustering is one of the most important analysis tasks in spatial databases. However, in many real applications, it is more meaningful constrained clustering objects on a spatial network (e.g. road network including traffic information). The existing methods don't refer to the constrained condition. It is therefore difficult to apply them to a real road network. This paper proposes the model of clustering objects in a road network with constrained conditions, giving the constrained clustering algorithm. The experimental results show that the algorithms achieves high efficiency. © 2008 IEEE.