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Survey on Partition based Clustering Algorithms in Big Data

E. Mahima Jane1 , E. George Dharma Prakash Raj2

  1. Department of Computer Application , Madras Christian College, Tambaram, India.
  2. Department of Computer Science and Engineering, Bharathidasan University, Trichy, India.

Correspondence should be addressed to: georgeprakashraj@yahoo.com.

Section:Survey Paper, Product Type: Journal Paper
Volume-5 , Issue-12 , Page no. 323-325, Dec-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i12.323325

Online published on Dec 31, 2017

Copyright © E. Mahima Jane , E. George Dharma Prakash Raj . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: E. Mahima Jane , E. George Dharma Prakash Raj, “Survey on Partition based Clustering Algorithms in Big Data,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.323-325, 2017.

MLA Style Citation: E. Mahima Jane , E. George Dharma Prakash Raj "Survey on Partition based Clustering Algorithms in Big Data." International Journal of Computer Sciences and Engineering 5.12 (2017): 323-325.

APA Style Citation: E. Mahima Jane , E. George Dharma Prakash Raj, (2017). Survey on Partition based Clustering Algorithms in Big Data. International Journal of Computer Sciences and Engineering, 5(12), 323-325.

BibTex Style Citation:
@article{Jane_2017,
author = {E. Mahima Jane , E. George Dharma Prakash Raj},
title = {Survey on Partition based Clustering Algorithms in Big Data},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2017},
volume = {5},
Issue = {12},
month = {12},
year = {2017},
issn = {2347-2693},
pages = {323-325},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1624},
doi = {https://doi.org/10.26438/ijcse/v5i12.323325}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i12.323325}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1624
TI - Survey on Partition based Clustering Algorithms in Big Data
T2 - International Journal of Computer Sciences and Engineering
AU - E. Mahima Jane , E. George Dharma Prakash Raj
PY - 2017
DA - 2017/12/31
PB - IJCSE, Indore, INDIA
SP - 323-325
IS - 12
VL - 5
SN - 2347-2693
ER -

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Abstract

Clustering is the task of dividing the data points into a number of groups such that data points in the same groups are more similar to other data points in the same group than those in other groups. As Big Data is referring to terabytes and petabytes of data and clustering algorithms are come with high computational costs, the question is how to cope with this problem and how to deploy clustering techniques to big data and get the results in a reasonable time. This paper focuses on the traditional partition based clustering algorithms such as KMeans, K Medoids, PAM, CLARA and CLARANS and its advantages and disadvantages.

Key-Words / Index Term

K-Means, PAM, CLARA, CLARANS

References

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