SUDBC: a Quickly Clustering Algorithm Based on Spatial Unit Density
Xiao Liu · Mini-micro Systems · 2005
With the rapid increase of data scale in databases,it is required that clustering algorithms have high efficiency,extensibility,ability to deal with arbitrary shapes of clusters,and non-sensitivity to noise data.In this paper,we propose a quickly clustering algorithm SUDBC based on spatial unit density. It first partitions the data space to be clustered into a set of spatial units. Then,it merges all neighbor units into the same clusters based on the spatial unit density.Therefore,the algorithm can deal with the large scalability of points.Experimental results confirm that SUDBC algorithm has the feature of dealing with arbitrary shape of data and non-sensitivity to noise data.