Cluster analysis is an essential tool in data mining. Several clustering algorithms have been
proposed and implemented, most of which are able to find good quality clustering results …

Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

In cluster analysis, a fundamental problem is to determine the best estimate of the number of
clusters; this is known as the automatic clustering problem. Because of lack of prior domain …

The application of several swarm intelligence and evolutionary metaheuristic algorithms in
data clustering problems has in the past few decades gained wide popularity and …

In the field of data mining, clustering has shown to be an important technique. Numerous
clustering methods have been devised and put into practice, and most of them locate high …

Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …

Kmeans-type clustering aims at partitioning a data set into clusters such that the objects in a
cluster are compact and the objects in different clusters are well separated. However, most …

In recent years, the dramatic rise in the use of the web and the improvement in
communications in general have transformed our society into one that strongly depends on …

The paper aims to shed some light on the question why clustering algorithms, despite being
quantitative and hence supposedly objective in nature, yield different and varied results. To …