본문 바로가기
  • Home

Personalized e-Commerce Recommendation System using RFM method and Association Rules

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2010, 15(12), pp.227-235
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

진병운 1 조영성 2 류근호 3

1한국전자통신연구원
2동양공업전문대학교
3충북대학교

Accredited

ABSTRACT

This paper proposes the recommendation system which is advanced using RFM method and Association Rules in e-Commerce. Using a implicit method which is not used user's profile for rating, it is necessary for user to keep the RFM score and Association Rules about users and items based on the whole purchased data in order to recommend the items. This proposing system is possible to advance recommendation system using RFM method and Association Rules for cross-selling, and also this system can avoid the duplicated recommendation by the cross comparison with having recommended items before. And also, it's efficient for them to build the strategy for marketing and crm(customer relationship management). It can be improved and evaluated according to the criteria of logicality through the experiment with dataset collected in a cosmetic cyber shopping mall. Finally, it is able to realize the personalized recommendation system for one to one web marketing in e-Commerce.

Citation status

* References for papers published after 2023 are currently being built.