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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Bibliographic Details
Published in:	Pattern recognition Vol. 58; pp. 39 - 48
Main Authors:	Mahesh Kumar, K., Rama Mohan Reddy, A.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.10.2016
Subjects:	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
Online Access:	Get full text
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