Global Institute for Research & Education (GIFRE)
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contributions. First, a new clustering method called CLARANS (Clustering Large Applications based on RANdomized Search), whose aim is to identify spatial structures that may be present in the data. Experimental results indicate that, when compared with existing clustering methods, CLARANS is very efficient and effective. Second, investigate how CLARANS can handle not only point's objects, but also polygon objects efficiently.