An Integrated Approach for Exploring Path-Type Association Rules

This paper develops an effective approach by integrating an Artificial Neural Network–Self-Organizing Map (ANN-SOM) and Ant Theory to analyze possible path-type rules from the use of transaction data and the stocking of sections and displays. These derived rules can be viewed as popular paths taken more frequently while customers are shopping. By properly using these rules, management could benefit by further comprehending which customer groups and which products best contribute to increased profits; they should also be able to react more quickly to change than their competitors do.

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