期刊論文

學年 97
學期 2
出版(發表)日期 2009-06-01
作品名稱 An Axis-Shifted Grid-Clustering Algorithm
作品名稱(其他語言)
著者 張忠義; Chang, Chung-i; 林丕靜; Lin, Nancy P.; 詹念怡; Jan, Nien-yi
單位 淡江大學資訊工程學系
出版者 臺北縣:淡江大學
著錄名稱、卷期、頁數 淡江理工學刊=Tamkang journal of science and engineering 12(2),頁183-192
摘要 These spatial clustering methods can be classified into four categories: partitioning method, hierarchical method, density-based method and grid-based method. 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 to group similar spatial objects into classes on this obtained grid structure, is an efficient clustering algorithm. To cluster efficiently and simultaneously, to reduce the influences of the size and borders of the cells, a new grid-based clustering algorithm, an Axis-Shifted Grid-Clustering algorithm (ASGC), is proposed in this paper. This new clustering method combines a novel density-grid based clustering with axis-shifted partitioning strategy to identify areas of high density in the input data space. The main idea is to shift the original grid structure in each dimension of the data space after the clusters generated from this original structure have been obtained. The shifted grid structure can be considered as a dynamic adjustment of the size of the original cells and reduce the weakness of borders of cells. And thus, the clusters generated from this shifted grid structure can be used to revise the originally obtained clusters. The experimental results verify that, indeed, the effect of this new algorithm is less influenced by the size of cells than other grid-based ones and requires at most a single scan through the data.
關鍵字 Data Mining;Grid-Based Clustering;Significant Cell;Grid Structure;Coordinate Axis
語言 en
ISSN 1560-6686
期刊性質 國內
收錄於 EI
產學合作
通訊作者
審稿制度
國別 TWN
公開徵稿
出版型式 ,電子版
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