Temporal Association Rules with Exponential Smoothing Method

As electronic commerce progresses, the temporal association rule is developed from partitioned data sets by time to offer personalized services for customer`s interest. In this paper, we proposed a temporal association rule with exponential smoothing method that is giving higher weights to recent data than past data. Through simulation and case study, we confirmed that it is more precise than existing temporal association rules but consumes running time