Journal Article10.1002/WIDM.30
Density-based clustering
TL;DR: In this article, a density-based clustering is defined as the task of identifying groups or clusters in a data set, a cluster is a set of data objects spread in the data space over a contiguous region of high density of objects.
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Abstract: Clustering refers to the task of identifying groups or clusters in a data set. In density-based clustering, a cluster is a set of data objects spread in the data space over a contiguous region of high density of objects. Density-based clusters are separated from each other by contiguous regions of low density of objects. Data objects located in low-density regions are typically considered noise or outliers. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 231–240 DOI: 10.1002/widm.30
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Technologies > Structure Discovery and Clustering
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Tian Zhang,Raghu Ramakrishnan,Miron Livny +2 more
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TL;DR: Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) as discussed by the authors is a data clustering method that is especially suitable for very large databases.
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Mihael Ankerst,Markus M. Breunig,Hans-Peter Kriegel,Jörg Sander +3 more
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TL;DR: A new algorithm is introduced for the purpose of cluster analysis which does not produce a clustering of a data set explicitly; but instead creates an augmented ordering of the database representing its density-based clustering structure.
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