Revolutionizing supermarket services with hierarchical association rule mining

: pp. 547–556
Received: February 19, 2023
Accepted: April 04, 2023
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
National School of Commerce and Management (ENCG), University of Hassan II Casablanca
Laboratory of Information Technology and Modeling, Hassan II University, Faculty of sciences Ben M'sik
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.

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