|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 (firstname.lastname@example.org)
|Source Publication||Pattern Recognition Letters
|Keyword||Grid Based Clustering
Density Based Clustering
Massive Spatial Data
|Abstract||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.|
|Corresponding Author||Sun, Ruizhi (email@example.com)|
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.
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.
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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