Extraction of customer potential value using unpurchased items and in-store movements
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part III
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In this paper, we propose a pattern mining method using POS data. Firstly, we transform raw POS data into tree structured data, extract some promising patterns from it by using a multiobjective evolutionary algorithm (MOEA), and construct a decision tree model using these patterns and customer attributes. From our computational experiments using practical POS data obtained from a supermarket chain in Japan, we show that our method can mine some promising patterns. Further, these patterns are useful for constructing a better decision tree model to identify target customers.