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Weighted association rules considering item RFM scores  

Park, Hee-Chang (Department of Statistics, Changwon National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.21, no.6, 2010 , pp. 1147-1154 More about this Journal
Abstract
One of the important goals in data mining is to discover and decide the relationships between different variables. Association rules are required for this technique and it find meaningful rules by quantifying the relationship between two items based on association measures such as support, confidence, and lift. In this paper, we presented the evaluation criteria of weighted association rule considering item RFM scores as importance of items. Original RFM technique has been used most widely applied method using customer information to find the most profitable customers. And then we compared general association rule technique with weighted association rule technique through the simulation data.
Keywords
Data mining; weighted association rule; weighted confidence; weighted lift; weighted support;
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Times Cited By KSCI : 3  (Citation Analysis)
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