Temporal Association Rules with Exponential Smoothing Method


The KIPS Transactions:PartD, Vol. 11, No. 3, pp. 741-746, Jun. 2004
10.3745/KIPSTD.2004.11.3.741,   PDF Download:

Abstract

As electronic commerceprogresses, 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.


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Cite this article
[IEEE Style]
L. N. Byon, B. S. Park, J. H. Han, H. I. Jeong, C. S. Leem, "Temporal Association Rules with Exponential Smoothing Method," The KIPS Transactions:PartD, vol. 11, no. 3, pp. 741-746, 2004. DOI: 10.3745/KIPSTD.2004.11.3.741.

[ACM Style]
Lu Na Byon, Byoung Sun Park, Jeong Hye Han, Han Il Jeong, and Choon Seong Leem. 2004. Temporal Association Rules with Exponential Smoothing Method. The KIPS Transactions:PartD, 11, 3, (2004), 741-746. DOI: 10.3745/KIPSTD.2004.11.3.741.