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A product recommendation system based on adjacency data  

Kim, Jin-Hwa (Sogang Business School, Sogang University)
Byeon, Hyeon-Su (Department of Management and Administration, Baekseok Arts University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.1, 2011 , pp. 19-27 More about this Journal
Abstract
Recommendation systems are developed to overcome the problems of selection and to promote intention to use. In this study, we propose a recommendation system using adjacency data according to user's behavior over time. For this, the product adjacencies are identified from the adjacency matrix based on graph theory. This research finds that there is a trend in the users' behavior over time though product adjacency fluctuates over time. The system is tested on its usability. The tests show that implementing this recommendation system increases users' intention to purchase and reduces the search time.
Keywords
Clickstream data; data adjacency; recommendation system; web store;
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Times Cited By KSCI : 6  (Citation Analysis)
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1 Kruskal, J. B. and Wish, M. (1991). Multidimensional scaling. Beverly Hills, CA: Sage.
2 Moe, W. and Fader, P. S. (2002). Uncovering patterns in cybershopping. California Management Review, 43, 106-117.
3 Moe, W. and Fader, P. S. (2004). Dynamic conversion behavior at e-commerce sites. Management Science, 50, 326-335.   DOI   ScienceOn
4 Shang, Y., Ruml, W., Zhang, Y. and Fromherz, M. (2004). Localization from connectivity in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 15, 961-974.   DOI   ScienceOn
5 고봉성, 이석원, 허정 (2009). 생명보험사 텔레마케팅 효율성 제고에 관한연구. <한국데이터정보과학회지>, 20, 673-684.
6 김경재, 김병국 (2005). 데이터 마이닝을 이용한 인터넷 쇼핑몰 상품추천시스템. <한국지능정보시스템학회논문지>, 11, 191-205.
7 김연형, 이석원 (2009). 추천시스템을 이용한 이메일 효율성 제고에 관한 연구. <한국데이터정보과학회지>, 20, 1129-1143.
8 김재경, 안도현, 조윤호 (2005). 개인별 상품추천시스템, WebCF-PT: 웹마이닝과 상품계층도를 이용한 협업필터링. <경영정보학연구>, 15, 63-79.
9 신일순, 정부연, 김보은 (2002). <패널데이터를 이용한 e-Business 소비자행태 분석>, 연구보고 02-15, 정보통신정책연구원
10 이석준 (2009). 근접 이웃 선정 협력적 필터링 추천시스템에서 이웃 선정 방법에 관한 연구. <한국데이터정보과학회지>, 20, 809-818.
11 이희춘 (2009). 협력적 필터링 추천기법에서 이웃 수를 이용한 선호도 예측 정확도 향상. <한국데이터정보과학회지>, 20, 505-514.
12 Balabanovic, M. and Shoham, Y. (1997). Fab: Content-based, collaborative recommendation. Communications of the ACM, 40, 66-72.
13 Błazewicz, J., Pesch, E. and Sterna, M. (2005). A novel representation of graph structures in web mining and data analysis. Omega, 33, 65-71.   DOI   ScienceOn
14 Bucklin, R. E., Lattin, J. M., Ansari, A., Gupta, S., Bell, D., Coupey, E., Little, J. D. C., Mela, C., Montgomery, A. and Steckel, J. (2002). Choice and the internet: From clickstream to research stream. Marketing Letters, 13, 245-258.   DOI   ScienceOn
15 Condon, E., Golden, B., Lele, S., Raghavan, S. and Wasil, E. (2002). A visualization model based on adjacency data. Decision Support Systems, 33, 349-362.   DOI   ScienceOn
16 Eirinaki, M. and Vazirgiannis, M. (2003). Web mining for web personalization. ACM Transactions on Internet Technology, 3, 1-27.   DOI