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  4. Revolutionizing supermarket services with hierarchical association rule mining

Revolutionizing supermarket services with hierarchical association rule mining

MMC.
2023;
Volume 10, Number 2
: pp. 547–556
https://doi.org/10.23939/mmc2023.02.547
Received: February 19, 2023
Accepted: April 04, 2023

Mathematical Modeling and Computing, Vol. 10, No. 2, pp. 547–556 (2023)

Authors:
  1. M. Meftah
  2. S. Ounacer
  3. S. Ardchir
  4. M. El Ghazouani
  5. M. Azzouazi
1
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
2
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
3
National School of Commerce and Management (ENCG), University of Hassan II Casablanca
4
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
5
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of Sciences Ben M'Sik

The use of association rule mining techniques has become a focal point for many researchers seeking a better understanding of consumer behavior.  By analyzing the relationships between products and their placement in aisles, valuable insights can be gained into the factors that influence product preservation in large-scale distribution environments.  This approach has the potential to inform better decision-making processes and optimize product preservation outcomes, despite some limitations in the quality of the data available.  Additionally, a hybridization approach was adopted by incorporating transactions from clients participating in a loyalty program to encourage large-scale distributions to gain a better understanding of customer behavior and improve their purchasing strategies.  The goal of this research is to promote consistency between the real-world and virtual representations of customer behavior, ultimately leading to improved purchasing outcomes for large-scale distributions.

product preservation
hybridation approach
loyalty program
association rules
apriori
large-scale distribution
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