Data clustering: Algorithms and its applications
Data is useless if information or knowledge that can be used for further reasoning cannot be
inferred from it. Cluster analysis, based on some criteria, shares data into important, practical …
inferred from it. Cluster analysis, based on some criteria, shares data into important, practical …
A comprehensive survey of clustering algorithms
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 …
communication science, computer science and biology science. Clustering, as the basic …
An overview on clustering methods
TS Madhulatha - arXiv preprint arXiv:1205.1117, 2012 - arxiv.org
Clustering is a common technique for statistical data analysis, which is used in many fields,
including machine learning, data mining, pattern recognition, image analysis and …
including machine learning, data mining, pattern recognition, image analysis and …
A review of clustering algorithms for big data
K Djouzi, K Beghdad-Bey - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
Big data is usually defined by five (05) characteristics called 5Vs+ 1C (Volume, Velocity,
Variety, Veracity, Value and Complexity). It means to data that are too large, dynamic and …
Variety, Veracity, Value and Complexity). It means to data that are too large, dynamic and …
A short review on different clustering techniques and their applications
In modern world, we have to deal with huge volumes of data which include image, video,
text and web documents, DNA, microarray gene data, etc. Organizing such data into rational …
text and web documents, DNA, microarray gene data, etc. Organizing such data into rational …
On clustering validation techniques
M Halkidi, Y Batistakis, M Vazirgiannis - Journal of intelligent information …, 2001 - Springer
Cluster analysis aims at identifying groups of similar objects and, therefore helps to discover
distribution of patterns and interesting correlations in large data sets. It has been subject of …
distribution of patterns and interesting correlations in large data sets. It has been subject of …
A taxonomy of machine learning clustering algorithms, challenges, and future realms
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 …
clustering methods have been devised and put into practice, and most of them locate high …
An overview of clustering methods
MGH Omran, AP Engelbrecht… - Intelligent Data …, 2007 - content.iospress.com
Data clustering is the process of identifying natural groupings or clusters within
multidimensional data based on some similarity measure. Clustering is a fundamental …
multidimensional data based on some similarity measure. Clustering is a fundamental …
Comparative study of single linkage, complete linkage, and ward method of agglomerative clustering
S Sharma, N Batra - … on machine learning, big data, cloud …, 2019 - ieeexplore.ieee.org
Clustering is the process of grouping the datasets into various clusters in such a way which
leads to maximum inter-cluster dissimilarity but maximum intra-cluster similarity. Clustering …
leads to maximum inter-cluster dissimilarity but maximum intra-cluster similarity. Clustering …
A survey of clustering algorithms for an industrial context
AC Benabdellah, A Benghabrit, I Bouhaddou - Procedia computer science, 2019 - Elsevier
Across a wide variety of fields and especially for industrial companies, data are being
collected and accumulated at a dramatic pace from many different resources and services …
collected and accumulated at a dramatic pace from many different resources and services …