A deflected grid-based algorithm for clustering analysis

Authors:
Nancy P. Lin;Chung-I Chang;Hao-En Chueh;Hung-Jen Chen;Wei-Hua Hao
Affiliations:
Department of Computer Science and Information Engineering, Tamkang University, Taipei County, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei County, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei County, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei County, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taipei County, Taiwan, R.O.C.
Venue:
WSEAS Transactions on Computers
Year:
2008

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Abstract

The grid-based clustering algorithm, which partitions the data space into a finite number of cells to form a grid structure and then performs all clustering operations on this obtained grid structure, is an efficient clustering algorithm, but its effect is seriously influenced by the size of the cells. To cluster efficiently and simultaneously, to reduce the influences of the size of the cells, a new grid-based clustering algorithm, called DGD, is proposed in this paper. The main idea of DGD algorithm is to deflect the original grid structure in each dimension of the data space after the clusters generated from this original structure have been obtained. The deflected grid structure can be considered a dynamic adjustment of the size of the original cells, and thus, the clusters generated from this deflected grid structure can be used to revise the originally obtained clusters. The experimental results verify that, indeed, the effect of DGD algorithm is less influenced by the size of the cells than other grid-based ones.