Pattern Mining in POS Data using a Historical Tree

Abstract

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