DBSCAN

Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, J… (More)
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Topic mentions per year

Topic mentions per year

1996-2018
05010015019962018

Papers overview

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2015
2015
Clustering algorithms are being the core topic of many fields of study in Computational Intelligence and Informatics. Their… (More)
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2015
2015
Clustering algorithms in the field of data-mining are used to aggregate similar objects into common groups. One of the best-known… (More)
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2013
2013
With the advent of Web 2.0, we see a new and differentiated scenario: there is more data than that can be effectively analyzed… (More)
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2012
2012
DBSCAN is a well-known density-based clustering algorithm which offers advantages for finding clusters of arbitrary shapes… (More)
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Highly Cited
2011
Highly Cited
2011
Data clustering is an important data mining technology that plays a crucial role in numerous scientific applications. However, it… (More)
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2010
2010
According to the efficiency bottleneck of algorithm DBSCAN, we present P-DBSCAN, a novel parallel version of this algorithm in… (More)
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2010
2010
The majority of data available in most disciplines is unlabeled and unclassified. The amount of data is often massive, hence… (More)
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Highly Cited
2007
Highly Cited
2007
This paper presents a new density-based clustering algorithm, ST-DBSCAN, which is based on DBSCAN. We propose three marginal… (More)
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Highly Cited
2004
Highly Cited
2004
Spatial data clustering is one of the important data mining techniques for extracting knowledge from large amount of spatial data… (More)
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Highly Cited
1996
Highly Cited
1996
Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large… (More)
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