GRIDEN: An effective grid-based and density-based spatial clustering algorithm to support parallel computing

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	GRIDEN: An effective grid-based and density-based spatial clustering algorithm to support parallel computing
	Deng, Chao; Song, Jinwei; Sun, Ruizhi; Cai, Saihua; Shi, Yinxue; Sun, Ruizhi (sunruizhi@cau.edu.cn)
作者部门	空间技术部
发表期刊	Pattern Recognition Letters
	2018
卷号	109 页码:81-88
ISSN	0167-8655
语种	英语
关键词	Grid Based Clustering Density Based Clustering Dbscan Griden Data Mining Massive Spatial Data Parallel Computing
摘要	Density-based clustering has been widely used in many fields. A new effective grid-based and density-based spatial clustering algorithm, GRIDEN, is proposed in this paper, which supports parallel computing in addition to multi-density clustering. It constructs grids using hyper-square cells and provides users with parameter k to control the balance between efficiency and accuracy to increase the flexibility of the algorithm. Compared with conventional density-based algorithms, it achieves much higher performance by eliminating distance calculations among points based on the newly proposed concept of Ε-neighbor cells. Compared with conventional grid-based algorithms, it uses a set of symmetric (2k+1)D cells to identify dense cells and the density-connected relationships among cells. Therefore, the maximum calculated deviation of Ε-neighbor points in the grid-based algorithm can be controlled to an acceptable level through parameter k. In our experiments, the results demonstrate that GRIDEN can achieve a reliable clustering result that is infinite closed with respect to the exact DBSCAN as parameter k grows, and it requires computational time that is only linear to N. © 2017 Elsevier B.V.
收录类别	SCI ; EI
文献类型	期刊论文
条目标识符	http://ir.nssc.ac.cn/handle/122/6143
专题	空间技术部
通讯作者	Sun, Ruizhi (sunruizhi@cau.edu.cn)
推荐引用方式 GB/T 7714	Deng, Chao,Song, Jinwei,Sun, Ruizhi,et al. GRIDEN: An effective grid-based and density-based spatial clustering algorithm to support parallel computing[J]. Pattern Recognition Letters,2018,109:81-88.
APA	Deng, Chao,Song, Jinwei,Sun, Ruizhi,Cai, Saihua,Shi, Yinxue,&Sun, Ruizhi .(2018).GRIDEN: An effective grid-based and density-based spatial clustering algorithm to support parallel computing.Pattern Recognition Letters,109,81-88.
MLA	Deng, Chao,et al."GRIDEN: An effective grid-based and density-based spatial clustering algorithm to support parallel computing".Pattern Recognition Letters 109(2018):81-88.

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