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Multidimensional Quantitative Rule Generation Algorithm for Transactional Database

by R. Sridevi, E. Ramaraj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 2
Year of Publication: 2014
Authors: R. Sridevi, E. Ramaraj
10.5120/17349-7812

R. Sridevi, E. Ramaraj . Multidimensional Quantitative Rule Generation Algorithm for Transactional Database. International Journal of Computer Applications. 99, 2 ( August 2014), 40-44. DOI=10.5120/17349-7812

@article{ 10.5120/17349-7812,
author = { R. Sridevi, E. Ramaraj },
title = { Multidimensional Quantitative Rule Generation Algorithm for Transactional Database },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 2 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 40-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number2/17349-7812/ },
doi = { 10.5120/17349-7812 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:10.790697+05:30
%A R. Sridevi
%A E. Ramaraj
%T Multidimensional Quantitative Rule Generation Algorithm for Transactional Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 2
%P 40-44
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is a technology development in the present decade for guiding decision making. One of the main applications of data mining is exploration of Association Rules. The objective of the research is to find out the association rules for the sample dataset to find out the interesting and useful rules. A lot of modifications have been suggested over the last two decades for the traditional Market Basket Analysis Algorithm like Apriori, FP -Growth, E-clat etc. The proposed Multidimensional Quantitative Rule Generation (MQRG) method is to generate more number of interesting rules that satisfy minimum confidence threshold (min_conf). This paper presents the comparison results of the existing algorithm with the proposed Multidimensional Quantitative Rule generation.

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Index Terms

Computer Science
Information Sciences

Keywords

Data mining Data Discretization Multidimensional Quantitative Association rules

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