Dynamic Expert Group Models for Recommender Systems

Author:

Kim DaeEun,Kim Sea Woo

Publisher

Springer Berlin Heidelberg

Reference9 articles.

1. J.S. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, pages 43–52, 1998.

2. J. Delgado, N. Ishii, and T. Ura. Content-based collaborative information filtering: Actively learning to classify and recommend documents. In Proceedings of Cooperative Information Agents, pages 206–215, 1998.

3. D. Kim and S.W. Kim. Dynamic models of expert groups to recommend web documents. In Proceedings of the 5th European Conference on Research and Advanced Technology for Digital Libraries, Darmstadt, 2001. Springer.

4. W. Hill, L. Stead, M. Rosenstein, and G. Furnas. Recommending and evaluating choices in a virtual community of use. In Proceedings of ACM CHI’95, pages 194–201, 1995.

5. S.W. Kim and C.W. Chung. Web document ranking by differentiated expert group evaluation. In Proceedings of the 9th International Conference on Human-Computer Interaction, 2001.

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1. Opinion Leader Based Filtering;Digital Libraries: Implementing Strategies and Sharing Experiences;2005

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