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Social Commerce Food Coupon Recommending System Based On Context Information Using Bayesian Network

베이지안 네트워크를 이용한 상황정보에 기반을 둔 소셜커머스 음식 쿠폰 추천시스템

  • 정현주 (공주대학교 컴퓨터공학과 컴퓨터소프트웨어전공) ;
  • 이상용 (공주대학교 컴퓨터공학부)
  • Received : 2013.01.18
  • Accepted : 2013.03.20
  • Published : 2013.03.31

Abstract

More sales of food and beverage coupons have been made using SNS on social commerce recently. If one buys coupons on social commerce, he/she can enjoy products at a lower price; however, there are drawbacks that one must consider such as location, service hours, and discount rate. Thus, this paper suggests a system that recommends food and beverage coupons on social commerce for users that considers a user's personal context of location, time, and purchase history. In order to reflect a user's context awareness and continuous preference, this paper suggests a method based on the Bayesian network. In order to reflect personalized weighting on the standard of coupon selection to match a user's preference, a measurement and classification of weighting preferences is performed on the basis of AHP. 20 experiments in one month involving 12 students were carried out to verify the effectiveness of the system, resulting in an 80% satisfaction level.

Keywords

Bayesian Network;Context Information;Social Commerce;SNS;Food Coupon

Acknowledgement

Supported by : 한국연구재단