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Reseach Article

Optimizing Association Rule using Genetic Algorithm and Data Sampling Approach

by Devyani Ojha, Pragya Pandey
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 11
Year of Publication: 2018
Authors: Devyani Ojha, Pragya Pandey
10.5120/ijca2018916083

Devyani Ojha, Pragya Pandey . Optimizing Association Rule using Genetic Algorithm and Data Sampling Approach. International Journal of Computer Applications. 179, 11 ( Jan 2018), 15-19. DOI=10.5120/ijca2018916083

@article{ 10.5120/ijca2018916083,
author = { Devyani Ojha, Pragya Pandey },
title = { Optimizing Association Rule using Genetic Algorithm and Data Sampling Approach },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 179 },
number = { 11 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number11/28843-2018916083/ },
doi = { 10.5120/ijca2018916083 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:55:03.457705+05:30
%A Devyani Ojha
%A Pragya Pandey
%T Optimizing Association Rule using Genetic Algorithm and Data Sampling Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 11
%P 15-19
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper work the association rules are optimized in order to find most suitable rules from the number of association rule generation algorithms. In this context most frequently used association rule mining algorithms are targeted for study namely Apriori and FP-tree. Basically the association rules are developed using transactional datasets. Additionally the number of generated rules in Apriori is large enough; on the other hand the FP-tree algorithm generates a main tree and additional trees. Such kind of tree generate confuse the experimenter. Therefore in this work a concept is proposed by which the optimal rules from both the set of rules are selected for applications. In this context two different concepts of the rule selection techniques are used first technique usages the sampling technique and second directly usage the outcomes of the Apriori and FP-Tree algorithm and make search from one algorithm’s rule set to others. In order to perform the search genetic algorithm is used which is used for optimal solution selection. According to the results sampling based technique needs additional computational resources as compared to genetic algorithm based technique due to additional evaluation cycles. But both the algorithms are effectively capable to reduce the amount of rules generated by the selected algorithms.

References
  1. Dhanalakshmi. D and Dr. J. Komala Lakshmi, “A Survey on Data Mining Research Trends”, A Survey on Data Mining Research Trends, Volume 3, Issue 10 October, 2014 Page No. 8911-8919
  2. Berson, Alex, and Stephen J. Smith, Building data mining applications for CRM, McGraw-Hill, Inc., 2002.
  3. Agrawal, Rakesh, and Ramakrishnan Srikant, "Fast algorithms for mining association rules." Proc. 20th international conference very large data bases, VLDB, Volume 1215, 1994.
  4. “Association Rules Mining”, available online at: https://www.vskills.in/certification/tutorial/data-mining-and-warehousing/association-rules-mining/
  5. Rana Ishita and Rana Ishita, “Frequent Itemset Mining in Data Mining: A Survey”, International Journal of Computer Applications (IJCA), Volume 139 – No.9, April 2016
  6. Sanjaydeep Singh Lodhi and Premnarayan Arya, “Frequent Itemset Mining Technique in Data Mining”, International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012
  7. Borgelt, Christian. "Frequent item set mining", Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2.6 (2012): pp. 437-456.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Association Rule FP-Tee Apriori Frequent Pattern mining Association Rule Mining Genetic Algorithm