Journal of KIISE:Computing Practices and Letters (한국정보과학회논문지:컴퓨팅의 실제 및 레터)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지

A Personalized Service System based on Distributed Heterogeneous Internet Shopping Mall Environment

분산 이기종 인터넷 쇼핑몰 환경에서의 벡터 모델 기반 개인화 서비스 시스템

  • Published : 2002.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we design and implement a system that presents a method for selecting and providing personalized services independently without unifying the existing system platform with shopping malls joined in the hub site. This system provides a mechanism for gathering information left behind by many clients visiting Web sites for analysis of customers property, vector model for selecting personalized services, and mechanism for providing them to customers who visited in a shopping mall joined to the hub site. In a position of shopping mall site, this kind of personalization system can provide target advertisement, point marketing, and point share service etc. without changing existing shopping mall's environment through wrapper web server. Hub site customers can get personalized services from many shopping mall sites with only once registration for the hub site.

본 논문에서는 서로 다른 플랫폼으로 구성된 허브 사이트 가맹점들이 지역적으로 분산되어 있는 분산 이기종 환경에서 각 가맹점들의 기존 플랫폼을 통일시키지 않고 독립적으로 고객이 관심을 가질만한 맞춤 정보 및 광고를 선정하여 제공하기 위한 시스템 설계 및 구현 내용을 서술한다. 본 논문에서 제안하는 시스템은 각 가맹점을 방문하는 고객들의 정보를 수집하기 위한 모니터링 기능, 고객 개개인의 특성에 맞는 서비스를 선정하기 위한 벡터 모델, 그리고 벡터 모델을 이용하여 선정된 서비스를 허브사이트 또는 각 가맹점을 방문하는 고객 개개인에게 제공하기 위한 기능을 지원한다. 본 시스템은 상점 입장에서는 허브 사이트 가맹점이 됨으로써 기존 플랫폼을 바꾸지 않고도 통합 서비스 및 개인화 서비스 제공이 가능하며, 고객 입장에서는 한번의 고객 등록으로 맞춤 서비스를 제공받을 수 있다는 장점을 갖는다.

Keywords

References

  1. Mobasher, B., et al., Autmatic Personalization Based on Web Usage Mining, Comm. of the ACM, Vol. 43(8), Aug. 2000 https://doi.org/10.1145/345124.345169
  2. G.-H. Yan, et al., Toolkits for a Distributed, Agent-Based Web Commerce System, In International IFIP Working Conference on Trends in Distributed Systems for Electronic Commerce(TrEC '98), Hamburg, Germany, June 1998
  3. Allen Cliff, et al., Internet World Guide to One-to-One Web Marketing, John Wiley & Sons, Inc., 1998
  4. 통계청 서비스업통계과, 전자상거래 통계조사 결과 2000년 7, 8월 사이버쇼핑몰조사, 통계청, 2000. 10, http://www.nso.go.kr/report/data/suec0010.htm
  5. Udi Manber et al., Experience with Personalization on Yahoo!, Comm. of the ACM, Vol. 43(8), Aug. 2000 https://doi.org/10.1145/345124.345136
  6. 아마존, http://www.amazone.com
  7. CDNOW, http://www.cdnow.com
  8. Wholesale Hub, http://www.wholesalehub.com
  9. Maurice D. Mulvenna et al., Personalization on the Net using Web Mining, Comm. of the ACM, Vol. 43(8), Aug. 2000 https://doi.org/10.1145/345124.345165
  10. J. Ben Schafer, Joseph Konstan, John Riedl, Recommender Systems in E-Commerce, In Proceedings of ACM E-Commerce, 1999 https://doi.org/10.1145/336992.337035
  11. Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl, Analysis of Recommendation Algorithms for E-Commerce, In Proceedings of ACM E-Commerce, 2000 https://doi.org/10.1145/352871.352887
  12. Myra Spiliopoulou, Web Usage Mining for Web Site Evaluation, Comm. of the ACM, Vol. 43(8), Aug. 2000 https://doi.org/10.1145/345124.345167
  13. Gediminas Adomavicius, Alexander Tuzhilin, User Profiling in Personalization Applications through Rule Discovery and Validation, Conference on Knowledge Discovery in Data, Aug. 1999 https://doi.org/10.1145/312129.312287
  14. Good, N., Schafer, B., Konstan, J., Borchers, A., Sarwar, B., Herlocker, J., and Riedl, J., Combining Collaborative Filtering with Personal Agents for Better Recommendations, In Proceedings of the AAI-'99 conference, 1999
  15. Ee-Peng Lim, Wee-Keong Ng, An Overview of the Agent-Based Electronic Commerce System (ABECOS) Project, Bulletin of the Technical Committee on Data Engineering, Vol. 23(1), Mar. 2000
  16. 온빛시스템, http://www.onbit.com
  17. 마이 야후!, http://www.myyahoo.com
  18. Music Machines, http://machines.hyperreal.org
  19. Broadvision, http://www.broadvision.com
  20. Shardanand, U. and Maes, P. Social information filtering: algorithms for automating word of mouth., In Proceedings of the ACM CHI Conference, 1995 https://doi.org/10.1145/223904.223931
  21. Net Perceptions, http://www.netperceptions.com
  22. Alper Caglayan et al., Learn Sesame a Learning Agent Engine Applied Artificial Intelligence, Vol. 11, pp. 393-412, 1997 https://doi.org/10.1080/088395197118109
  23. Michelle A. Hoyle and Christopher Lueg, Open Sesame!: A Look at Personal Assistants, Proceedings of the Practical Application of Intelligent Agents and Multi-Agent Technology(PAAM 97), April. 1997
  24. Robert Armstrong et al., WebWatcher: A Learning Apprentice for the World Wide Web, AAAI Spring Symposium on Information Gathering, March. 1997
  25. J. Konstan et al., GroupLens:Applying collaborative filtering to Usenet news, Communications of the ACM, 40(3), pp. 77-87, 1997 https://doi.org/10.1145/245108.245126
  26. Bamshad Mobasher et al., Discovery of aggregate usage profile for web personalization, In Proceedings of the WebKDD Workshop, 2000
  27. Lyle H et al., Clustering methods for collaborative filtering, In Workshop in Recommendation Systems at the 15th National Conference on Artificial Intelligence, 1998
  28. 김종우, 이경미, 김영국, 유관종, 인터넷 상점에서의 실시간 개인화된 광고 제공 기법, 경영정보학연구 제9권 제4호, 1999년 12월
  29. 박성준, 김주연, 김영국, 인터넷 쇼핑몰 허브 사이트를 위한 개인화된 맞춤 서비스 제공 시스템, 한국정보과학회 추계학술발표논문집, 제27권 2호, 2000년 10월
  30. Karl Avedal et al., Professional JSP, Wrox Press, 2000
  31. Marty Hall, Core Servlets and Java Server Pages, Prentice-Hall, Inc., 2000
  32. 윤혜숙, 김영국, 최훈, 홍승재, 복수의 인터넷 쇼핑몰에서 통용되는 안전한 전자상거래 지불수단으로서 로열티시스템, 한국정보처리학회 논문지 제7권 제5호, 2000년 5월
  33. Cynthia Bloch and Stephanie Bodoff, The Java Tutorial Continued: Servlets, http://java.sun.com/docs/books/tutorial/servlets/index.html
  34. Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Modern Information Retireval, Addison Wesley Ltd., 1999
  35. Sander M. Bohte et al., On Current Technology for Information Filtering and User Profiling in Agent-Based Systems, Part I: A Perspective, short reports on Current Tech. for information Filtering and User Profiling in Agent-Based Systems, Jan., 2000