IRCI Article ID: IRCI-AR-0000002601

Modified Genetic Algorithm and Association Rule Mining for the Retail Sector

Journal: Journal of Information Systems and Informatics

Publication: 2023-09-11 · Vol. 5 No. 3 · pp. 1099–1110

DOI: 10.51519/journalisi.v5i3.561

Cite this article

Citation

Choose a citation style or copy BibTeX for your reference manager.

 
View Original Publication

Abstract

This paper concentrates on the optimization of elementary association rule mining. The basic approach of association rule mining generates the positive association rule but focusing on both positive and negative association rule mining to find out efficient results is lacking. Thus our aim is to provide an approach to optimize all positive and negative association rules with the help of a modified genetic algorithm. A genetic algorithm is an optimization technique that provides the best possible solutions that are stronger than the other solutions. The present approach focuses on the importance of population through mean fitness value for further genetic algorithm operation. This paper also shows a comparison between normal Apriori, the Genetic Algorithm, and our proposed algorithm. Where in as a result the proposed approach worked better than others. We believe that the proposed methodology would increase the efficiency of the Decision support system of retail stores.

0
IRCI Cited By
0
Indexed References

Authors

References

No references were harvested yet.

Cited By (0)

No indexed citing article has been matched by IRCI yet.