A study on email efficiency on recommendation system

추천시스템을 이용한 이메일 효율성 제고에 관한 연구

  • Kim, Yon-Hyong (Department of Public Survey and Applied Statistics, Jeonju University) ;
  • Lee, Seok-Won (Department of Public Survey and Applied Statistics, Jeonju University)
  • 김연형 (전주대학교 여론정보통계학과) ;
  • 이석원 (전주대학교 여론정보통계학과)
  • Published : 2009.11.30

Abstract

This paper proposes a recommendation system (Association Rule System for Targeting) which considers target which is not considered by previous Logistic Regression system, and proves that the efficiency of the recommendation system is better than that of the current and previous Apriori algorithm system. Also this study shows that the click and purchasing rate of the proposed Association Rule System for Targeting is much higher than those of current Apriori algorithm system after the purchasing campaign even though the open rate of the former is lower than that of the latter. In comparison with Logistic Regression methodology, this paper proves with experimental data that the purchasing effect of the proposed system for specific items is much higher in accuracy than that of current Apriori algorithm system even though the purchasing rate of current Apriori algorithm system is higher in whole shopping malls than that of the proposed Association Rule System for Targeting.

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