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A Study on Milestones of Association Rule Mining Algorithms in Large Databases

by Saravanan Suba, Chistopher.t
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 3
Year of Publication: 2012
Authors: Saravanan Suba, Chistopher.t
10.5120/7167-9674

Saravanan Suba, Chistopher.t . A Study on Milestones of Association Rule Mining Algorithms in Large Databases. International Journal of Computer Applications. 47, 3 ( June 2012), 12-19. DOI=10.5120/7167-9674

@article{ 10.5120/7167-9674,
author = { Saravanan Suba, Chistopher.t },
title = { A Study on Milestones of Association Rule Mining Algorithms in Large Databases },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 3 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 12-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number3/7167-9674/ },
doi = { 10.5120/7167-9674 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:40:55.228733+05:30
%A Saravanan Suba
%A Chistopher.t
%T A Study on Milestones of Association Rule Mining Algorithms in Large Databases
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 3
%P 12-19
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining helps in doing automated extraction and generating predictive information from large amount of data. The association rule mining is one of the important area of research in Data mining. The Association rule mining identifies the useful associations or relationship among big set of data items. In this paper, we provide the important concepts of Association rule mining and existing algorithms and their effectiveness and drawbacks. The references provided in this paper covered the main theoretical issues and guiding the researcher in an interesting research direction that have yet to be discovered.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Association Rule Mining Apriori Fp-growth Frequent Item Sets

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