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http://dx.doi.org/10.3745/KIPSTD.2004.11D.3.741

Temporal Association Rules with Exponential Smoothing Method  

Byon, Lu-Na (충북대학교 대학원 통계학과)
Park, Byoung-Sun (한국표준과학연구원)
Han, Jeong-Hye (청주교육대학교 컴퓨터교육과)
Jeong, Han-Il (대전대학교 인터넷정보공학과)
Leem, Choon-Seong (연세대학교 정보산업학과)
Publication Information
The KIPS Transactions:PartD / v.11D, no.3, 2004 , pp. 741-746 More about this Journal
Abstract
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.
Keywords
I-Commerce; Association Rules; Temporal Association Rules; Exponential Smoothing Method;
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