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A Parallel Approach to Combined Association Rule Mining

by Zaid Makani, Sana Arora, Prashasti Kanikar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 15
Year of Publication: 2013
Authors: Zaid Makani, Sana Arora, Prashasti Kanikar
10.5120/10154-5004

Zaid Makani, Sana Arora, Prashasti Kanikar . A Parallel Approach to Combined Association Rule Mining. International Journal of Computer Applications. 62, 15 ( January 2013), 7-13. DOI=10.5120/10154-5004

@article{ 10.5120/10154-5004,
author = { Zaid Makani, Sana Arora, Prashasti Kanikar },
title = { A Parallel Approach to Combined Association Rule Mining },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 15 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number15/10154-5004/ },
doi = { 10.5120/10154-5004 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:11:51.491456+05:30
%A Zaid Makani
%A Sana Arora
%A Prashasti Kanikar
%T A Parallel Approach to Combined Association Rule Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 15
%P 7-13
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data Mining carried out using traditional methodologies of Support-Confidence framework and Association Rule Mining yield an enormous number of inefficient rules or patterns in a certain amount of time. In this paper, a parallel approach to Combined Mining has been implemented that not only generates rules which are "actionable" but also does so in a time period that is lesser than that of the traditional approach. These implementations are carried out on datasets at different locations consisting of multiple related data items and are independent of each other. The results of an Apriori algorithm is fed as an input to Combined Mining so as to generate more useful patterns for the process of business decision making. The results highlight that the two objectives of "Actionability" and "Efficiency with respect to time" are achieved using parallel approach to Combined Mining rather than compromising on one of them as in serial approach.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Combined Mining Parallel Combined Mining Sequential Combined Mining

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