Case-based Filtering by Using Degree of Membership for Digital Contents

디지털 콘텐츠를 위한 소속도를 이용한 사례기반 필터링

  • 김형일 (나사렛대학교 멀티미디어학과)
  • Received : 2010.10.04
  • Accepted : 2010.10.25
  • Published : 2010.10.28


As digital contents become vast in quantity, it takes long time for users to search the digital contents they want, which is a problem that has arisen. Therefore, it is required to have the technology that analyzes vast digital contents and extracts the appropriate contents for users in order to provide them with contents they want. For a fast searching of digital contents suitable for users, it is necessary to have the technology of filtering for digital contents. In this paper, we propose a method of filtering digital contents suitable for individual users. The method suggested in this paper is to analyze case-based information in digital contents and provide the digital contents suitable for individual users. The case for using digital contents is used for analysis of users' preference. Various simulations were conducted to confirm the effectiveness of the proposed method.


Digital Contents;Information Filtering;Collaborative Filtering;Personalization


Supported by : 나사렛대학교


  1. 이호영, 정은희, 이장혁, 웹2.0시대 디지털 콘텐츠의 사회적 확산 경로 연구, 정보통신정책연구원, 2007.
  2. 김진규, 윤재식, 김은정, 정우식, 이강년, 박성만, 김애경, 2010년 2분기 콘텐츠산업 동향분석보고서, 한국콘텐츠진흥원, 2010.
  3. J. Park and S. Hunting, XML Topic Maps: creating and using topic maps for the Web, Addison-Wesley, 2003.
  4. L. Maicher and J. Park, Charting the Topic Maps Research and Applications Landscape, Springer, 2006.
  5. J. Park and A. Cheyer, "Just For Me: Topic Maps and Ontologies," In Proceedings of the 1st International Workshop on Topic Maps Research and Applications, pp.145-159, 2005(10).
  6. S. Seedorf, A. Korthaus, and M. Aleksy, "Creating a Topic Map Query Tool for Mobile Devices using J2ME and XML," In Proceedings of the 4th International Symposium on Information and Communication Technologies, Vol.92, pp.111-116, 2005(1).
  7. N. Moraveji, A. Travis, M. Bidinost, and M. Halpern, "Designing an Integrated Review Sheet for an Electronic Textbook," In Proceedings of Conference on Human Factors in Computing Systems, pp.892-893, 2003(4).
  8. R. Wilson, "The Look and Feel of an Ebook: Considerations in Interface Design," In Proceedings of the 2002 ACM Symposium on Applied Computing, pp.530-534, 2002(3).
  9. S. K. Card, L. Hong, J. D. Mackinlay, and E. H. Chi, "3Book: A 3D Electronic Smart Book," In Proceedings of the Working Conference on Advanced Visual Interfaces, pp.303-307, 2004(5).
  10. S. K. Card, L. Hong, J. D. Mackinlay, and E. H. Chi, "3Book: A Scalable 3D Virtual Book," In Proceedings of Conference on Human Factors in Computing Systems, pp.1095-1098, 2004(4).
  11. Y. Chu, I. H. Witten, R. Lobb, and D. Bainbridge, "How to Turn the Page," In Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries, pp.186-188, 2003(5).
  12. S. V. Agoshkov and P. A. Dmitriev, "Electronic Publication Maintenance Systems," Programming and Computer Software, Vol.28, No.5, pp.293-300, 2002(9).
  13. J. Konstan, B. Millr, D. Maltz, J. Herlocker, L. Gordon, and J. Riedl, "GroupLens: Applying Collaborative Filtering to Usenet News," Communications of the ACM, Vol.40, No.3, pp.77-87, 1997(3).
  14. J. Breese, D. Heckerman, and C. Kadie, "Empirical Analysis of Predictive Algorithms for Collaborative Filtering," In Proceedings of the 14th Annual Conference on Uncertainty in Artificial Intelligence, pp.43-52, 1998(7).
  15. J. Herlocker, J. Konstan, A. Borchers, and J. Riedl, "An Algorithmic Framework for Performing Collaborative Filtering," In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.230-237, 1999(8).
  16. D. Billsus, and M. J. Pazzani, "Learning Collaborative Information Filters," In Proceedings of the 15th International Conference on Machine Learning, pp.46-54, 1998(7).
  17. B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, "Application of Dimensionality Reduction in Recommender System-A Case Study," In Proceedings of the ACM WebKDD Workshop, 2000(8).
  18. M. Deshpande and G. Karypis, "Item-Based Top-N Recommendation Algorithms," ACM Transaction on Information Systems, Vol.22, No.1, pp.143-177, 2004(1).
  19. B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, "Item-based Collaborative Filtering Recommendation Algorithms," In Proceedings of the 10th International WWW Conference, pp.285-295, 2001(5).
  20. G. Linden, B. Smith, and J. York, "Amazon. com Recommendations: Item-to-Item Collaborative Filtering," IEEE Internet Computing, pp.76-80, 2003(2).