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A Survey on Clustering Methods in Data Mining

by Bhagyashree Pathak, Niranjan Lal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 159 - Number 2
Year of Publication: 2017
Authors: Bhagyashree Pathak, Niranjan Lal

Bhagyashree Pathak, Niranjan Lal . A Survey on Clustering Methods in Data Mining. International Journal of Computer Applications. 159, 2 ( Feb 2017), 6-11. DOI=10.5120/ijca2017912747

@article{ 10.5120/ijca2017912747,
author = { Bhagyashree Pathak, Niranjan Lal },
title = { A Survey on Clustering Methods in Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 159 },
number = { 2 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2017912747 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:04:38.020577+05:30
%A Bhagyashree Pathak
%A Niranjan Lal
%T A Survey on Clustering Methods in Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 159
%N 2
%P 6-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

With increasing amount of data in information industry, there may be an immense amount from claiming information accessible in the majority of the business data. This information will be of no utilization until it is changed over under suitable data. It found important to examine this immense amount of data and withdrawal meaningful knowledge from it. Data mining is an important methodology in withdrawal of meaningful knowledge from large cluster of data. Clustering is included in the tasks of data mining. Clustering is one of the task in which making a group of physical objects into classes of similar objects. In this review paper, we give a study of various clustering methods in data mining for information retrieval and other purposes. We will describe fundamental study of clustering and will analyze each methodology by doing comparative study in table format and examine the clustering algorithms for heterogeneous data.

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Index Terms

Computer Science
Information Sciences


Data mining Clustering Clustering methods.