BorderProcessing Technique in GridBased Clustering
QIU BaoZhi1,2, SHEN JunYi1
1.School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049 2.School of Information and Engineering, Zhengzhou University, Zhengzhou 450052
Abstract In order to improve accuracy of gridbased clustering, a borderprocessing technique is proposed, Using restricted k nearest neighbors and concept of relative density. The technique enables us to separate cluster’s border points from outliers or noises accurately. Then, a gridbased clustering algorithm with border processing (GBCB) is developed. Experiment results show high accuracy of recognition of border points. Due to the only one data scan, the GBCB algorithm is very efficient with its run time being linear to the size of the input data set, and can discover arbitrary shapes of clusters and scale well.
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2006, Vol. 19 
