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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
Pattern Mining in POS Data using a Historical Tree
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2702-7
Takanobu Nakahara, Osaka Prefecture University
Hiroyuki Morita, Osaka Prefecture University
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.
Citation:
Takanobu Nakahara, Hiroyuki Morita, "Pattern Mining in POS Data using a Historical Tree," icdmw, pp.570-574, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
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