NPClu: An Approach for Clustering Non-point Objects

The vast majority of clustering algorithms and approaches deal with sets of objects, where objects are points in the multidimensional Euclidean space, each occupying zero hyper volume. There is a wealth of application domains that produce data sets in which the objects occupy hyperspace. Such application domains include spatiotemporal databases, medical applications etc. It is clear that clustering such data sets cannot be achieved by existing algorithms. In this paper we propose NPClu an approach for clustering sets of objects that are spatially extended. We experimentally evaluated the performance of our approach to show