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Discovery of Fuzzy Hierarchical Association Rules

by Reena Kumari, Jyoti Vashishtha
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 19
Year of Publication: 2014
Authors: Reena Kumari, Jyoti Vashishtha
10.5120/17292-7762

Reena Kumari, Jyoti Vashishtha . Discovery of Fuzzy Hierarchical Association Rules. International Journal of Computer Applications. 98, 19 ( July 2014), 20-26. DOI=10.5120/17292-7762

@article{ 10.5120/17292-7762,
author = { Reena Kumari, Jyoti Vashishtha },
title = { Discovery of Fuzzy Hierarchical Association Rules },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 19 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number19/17292-7762/ },
doi = { 10.5120/17292-7762 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:26:37.860007+05:30
%A Reena Kumari
%A Jyoti Vashishtha
%T Discovery of Fuzzy Hierarchical Association Rules
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 19
%P 20-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A number of techniques have been developed to turn data into useful knowledge. Most of the algorithms in data mining find association rules among transactions using binary values and at single concept level. However it will be more exciting to discover hierarchical association rules for decision makers. In this work we have integrated association rule mining with fuzzy set theory and hierarchy. We have proposed an algorithm to discover hierarchical fuzzy association rules. We have used different minimum support and membership functions at each level of hierarchy. We have also used a predefined taxonomy for multilevel of hierarchy.

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Index Terms

Computer Science
Information Sciences

Keywords

Hierarchical Fuzzy Association Rules Taxonomy Membership function

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