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A Comparative analysis of Association rule excavating in Big Data Mining Algorithms

Ahilandeeswari. G1 , DR.R.Manicka Chezian2

Section:Review Paper, Product Type: Journal Paper
Volume-3 , Issue-6 , Page no. 82-88, Jun-2015

Online published on Jun 29, 2015

Copyright © Ahilandeeswari. G, DR.R.Manicka Chezian . 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: Ahilandeeswari. G, DR.R.Manicka Chezian, “A Comparative analysis of Association rule excavating in Big Data Mining Algorithms,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.82-88, 2015.

MLA Style Citation: Ahilandeeswari. G, DR.R.Manicka Chezian "A Comparative analysis of Association rule excavating in Big Data Mining Algorithms." International Journal of Computer Sciences and Engineering 3.6 (2015): 82-88.

APA Style Citation: Ahilandeeswari. G, DR.R.Manicka Chezian, (2015). A Comparative analysis of Association rule excavating in Big Data Mining Algorithms. International Journal of Computer Sciences and Engineering, 3(6), 82-88.

BibTex Style Citation:
@article{G_2015,
author = {Ahilandeeswari. G, DR.R.Manicka Chezian},
title = {A Comparative analysis of Association rule excavating in Big Data Mining Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2015},
volume = {3},
Issue = {6},
month = {6},
year = {2015},
issn = {2347-2693},
pages = {82-88},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=555},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=555
TI - A Comparative analysis of Association rule excavating in Big Data Mining Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - Ahilandeeswari. G, DR.R.Manicka Chezian
PY - 2015
DA - 2015/06/29
PB - IJCSE, Indore, INDIA
SP - 82-88
IS - 6
VL - 3
SN - 2347-2693
ER -

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Abstract

In Data Mining Research, Association rule mining plays a significant role in data mining. This paper presents the review of Association rule mining. The analysis of research survey would give the instruction concerning somewhat has been done previously in the same area, what is the present tendency and what are the other related areas. Big data is the word for a set of data sets which are enormous and convoluted, it holds structured and unstructured both varieties of data. Data comes from everywhere, sensors used to amass climate information, posts to social media sites, digital pictures and videos etc. This data is known as big data. Useful data can elicit from this big data with the help of data mining. In this paper, the association rule of data mining and advanced big data mining algorithms are scrutinized.

Key-Words / Index Term

Association rule, Apriori Algorithm Big data mining, Data mining

References

[1] R. Agarwal and R. Srikant,“Fast Algorithms for Mining Association Rules.”, International Conference on very large Databases, proc 20th, pp 487-499, June 1994.
[2] Khurana K and Sharma S, ―A comparative analysis of association rule mining algorithms, International Journal of Scientific and Research Publications, Volume 3, Issue 5, pp 38-45, May 2013.
[3] Borgelt, C. “Efficient Implementations of Apriori and Eclat”. Workshop of frequent item set mining implementations (FIMI 2003, Melbourne, FL, USA).
[4] Hunyadi, D.”Performance comparison of Apriori and FP-Growth Algorithms in Generating Association Rules”.Proceedings of the European Computing Conference ISBN: 978-960-474-297-4.
[5] Thieme, S.L. “Algorithmic Features of Eclat”. FIMI, Volume 126 of CEUR Workshop Proceedings, CEUR- WS.org, 2004.
[6] Ms. Dhamdhere Jyoti L., Prof. Deshpande Kiran B. "An Effective Algorithm for Frequent Itemset Mining on Hadoop.", International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 8, August 2014.
[7] Agrawal, R., Shafer, J.C., "Parallel mining of association rules.", IEEE Transactions on Knowledge and Data Engineering, Volume.8, no.6, pp 962-969, Dec 1996.
[8] A. Swami, T. Imielienski, R. Agrawal," Mining Association Rules between Sets of Items in Large databases.", ACM Press, pp 207–216, July 1993
[9] Brain.s Motwani R,Ullman.J.D and S. Tsur,"Dynamic itemsets counting and implication rules for market basket analysis.", ACM-SIGMOD ,pages 255-264, May 1997.
[10] Ferenc Kovacs and Janos Illes “Frequent Itemset Mining on Hadoop.”,IEEE 9th International conference on Computational Cybernetics, Volume 2 Issue 4, June 2013.