Product-group Recommendation based on Association Rule Mining and Collaborative Filtering in Ubiquitous Computing Environment

유비쿼터스 환경에서 연관규칙과 협업필터링을 이용한 상품그룹추천

  • Published : 2007.08.31

Abstract

In ubiquitous computing environment such as ubiquitous marketplace (u-market), there is a need of providing context-based personalization service while considering the nomadic user preference and corresponding requirements. To do so, the recommendation systems should deal with the tremendous amount of context data. Hence, the purpose of this paper is to propose a novel recommendation method which provides the products-group list of the customers in u-market based on the shopping intention and preferences. We have developed FREPIRS(FREquent Purchased Item-sets Recommendation Service), which makes recommendation listof product-group, not individual product. Collaborative filtering and apriori algorithm are adopted in FREPIRS to build product-group.

Keywords

References

  1. 김재경, 조윤호, 김승태, 김혜경, "모바일 전자상거래 환경에 적합한 개인화된 추천시스템", 경영정보학연구, 제15권, 제3호(2005), pp.223-241
  2. 김지혜, 박두순, "연관규칙과 협업적 필터링을 이용한 상품 추천시스템 개발", 컴퓨터 교육학회 논문지, 제9권, 제1호(2006), pp.1-10
  3. 안현철, 한인구, 김경재, "연관규칙기법과 분류모형을 결합한 상품 추천시스템 : G 인터넷 쇼핑몰의 사례", Information Systems Review, Vol.8, No.1(2006), pp.181-199
  4. 황준현, 김재련, "역 연관규칙을 이용한 타겟 마케팅", 한국지능정보시스템학회논문지, 제9권, 제1호(2003), pp.195-209
  5. Han, J. and M. Kamber, Data Mining Concepts and Techniques, Morgan Kaufmann 2000
  6. Chen, A., "Context-Aware Collaborative Filtering System : Predicting the User's Preference in Ubiquitous Computing", LoCA 2005, LNCS 3479 (2005), pp.244-253
  7. El-khatib, K., Z. Zhang, N. Hadibi and G. Bochmann, "Personal and service mobility in ubiquitous computing environments", Wireless communications and mobile computing, Vol.4(2004), pp.595-605 https://doi.org/10.1002/wcm.231
  8. Hwang, J. H., M. S. Gu, and K. H. Ryu, "Context-Based Recommendation Service in Ubiquitous commerce", ICCSA 2005, LNCS 3481 (2005), pp.966-975
  9. Keegan, S. and G., O'Hare, "EasiShop : Enabiling uCommerce through Intelligenct Mobile Agent Technologies", LNCS 2881 (2003), pp.200-209
  10. Kim, H. K., K. J. Lee and J. K. Kim, "A Peer-to-Peer CF-Recommendation in Ubiquitous Environment", PRIMA 2006, LNAI 4088 (2006), pp.678-683
  11. Kurkovsky, S. and K. Harihar, "Using ubiquitous computing in interactive mobile marketing", Personal and Ubiquitous Computing, Vol.10, No.4(2006), pp.227-240 https://doi.org/10.1007/s00779-005-0044-5
  12. Lawrence, R. D., G. S. Almasi, V. Kotlyar, M. S. Viveros, and S. S. Duri, "Personalization of supermarket product recommendations", Data Mining and Knowledge Discovery, Vol.5(2001), pp.11-32 https://doi.org/10.1023/A:1009835726774
  13. Lee, J. K., J. K. Kim, S. H. Kim and H. K. Park, "An Intelligent Idea Categorizer for Electronic Meeting Systems", Group Decision and Negociation, Vol.11, No.5 (2002), pp.363-378 https://doi.org/10.1023/A:1020434111129
  14. McDonald, D. W., "Ubiquitous Recommendation Systems", Computer, Vol.36, No.10(2003), pp.111-112
  15. Roussos, G. and T. Moussouri, "Consumer perceptions of privacy, security and trust in ubiquitous commerce", Personal and Ubiquitous Computing, Vol.8, No.6 (2004), pp.416-429 https://doi.org/10.1007/s00779-004-0307-6
  16. Sarwar, B., G. Karypis, J. Konstan, and J. Riedl, "Analysis of Recommendation Algorithms for E-Commerce", Proceedings of the 2nd ACM conference on Electronic commerce (2000), pp.158-167
  17. Schafer, B., J. A. Konstan and J. Riedl, "E-commerce recommendation applications", Data Mining and Knowledge Discovery, Vol.5, No.1-2(2001), pp.115-153 https://doi.org/10.1023/A:1009804230409