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

•Propose a new effective density-based and grid-based clustering algorithm GRIDEN for massive spatial data.•Present a new concept of ε-neighbor cells to improve the clustering accuracy of grid-based algorithm.•Present a parallel computing algorithm for high dimensional density-based clustering to ac...

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Veröffentlicht in:	Pattern recognition letters Jg. 109; S. 81 - 88
Hauptverfasser:	Deng, Chao, Song, Jinwei, Sun, Ruizhi, Cai, Saihua, Shi, Yinxue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 15.07.2018 Elsevier Science Ltd
Schlagworte:	Algorithms Clustering Computer applications Computing time Data mining DBSCAN Delta cells Density Density-based clustering Grid-based clustering GRIDEN Massive spatial data Mathematical analysis Parallel computing Parallel processing Parameters Spatial data Massive spatial data GRIDEN Parallel computing DBSCAN Data mining Density-based clustering Grid-based clustering
ISSN:	0167-8655, 1872-7344
Online-Zugang:	Volltext
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