Revolutionizing supermarket services with hierarchical association rule mining

Abstract

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.