Bunching is imperative in information examination and information mining applications.
There are diverse kinds of bunches: Well-isolated groups, Center-based groups, Contiguous …

The density-based spatial clustering of applications with noise (DBSCAN) is regarded as a
pioneering algorithm of the density-based clustering technique. It provides the ability to …

The development of new technologies and methods of data collection produces the
necessity to summarise the large quantity of information that is available. Usually, we face a …

The density peaks (DP) clustering approach is a novel density-based clustering algorithm.
On the basis of the prior assumption of consistency for semi-supervised learning problems …

Clustering is one of the research hotspots in the field of data mining and has extensive
applications in practice. Recently, Rodriguez and Laio [1] published a clustering algorithm …

The current research on ensemble clustering mainly focuses on integration strategies, but
the attention regarding the measurement and optimization of basic cluster is less …

In recent years, the clustering of multi-density data has been a research hotspot. As a widely
applied clustering algorithm, density-based spatial clustering of application with noise …

This study performed a content analysis of data retrieved from 30 peer-reviewed scientific
publications (1996–2016) that describe the applied algorithm models for data wrangling in …

Aiming at the problem that the edge points are difficult to be accurately divided in the
DBSCAN algorithm, a density clustering algorithm based on silhouette coefficient constraints …

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