A fast DBSCAN clustering algorithm by accelerating neighbor searching using Groups method

Density based clustering methods are proposed for clustering spatial databases with noise. Density Based Spatial Clustering of Applications with Noise (DBSCAN) can discover clusters of arbitrary shape and also handles outliers effectively. DBSCAN obtains clusters by finding the number of points with...

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Vydané v:	Pattern recognition Ročník 58; s. 39 - 48
Hlavní autori:	Mahesh Kumar, K., Rama Mohan Reddy, A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.10.2016
Predmet:	Benchmarking Clustering Clusters Computation DBSCAN Density Density based clustering Neighborhood graph Noise Pattern recognition Searching Unsupervised learning DBSCAN Density based clustering Unsupervised learning Neighborhood graph
ISSN:	0031-3203, 1873-5142
On-line prístup:	Získať plný text
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