Affiliation:
1. Nancy Université, France
Abstract
The experiments conducted show that only 6 delegates are sufficient to accurately estimate ratings of the whole set of other users, which dramatically reduces the number of users classically required.
Reference67 articles.
1. Adomavicius G., Tuzhilin A. (2005). Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art, IEEE transactions on knowledge and data engineering, vol. 17, n° 6, p. 734-749.
2. Agarwal, N., Liu, H., Tang, L., and Yu, P. S. (2008). Identifying the influential bloggers in a community. In Proceedings of the international conference on Web search and web data mining (WSDM’08) (New York, NY, USA, 2008), ACM, pp. 207–218.
3. Aggarwal, C.C., Wolf, J., Wu, K.L. and Yu, P.S. (1999). Horting hatches an egg: a new graph-theoretic approach to collaborative filtering. Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining.
4. Ahn, H.J. (2008) A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem. Information Sciences 178, pp 37–51.
5. Allan, J., Aslam, J., Belkin, N., Buckley, C., Callan, J., & Croft, B. A. (2003). Challenges in information retrieval and language modeling. Report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, september 2002. ACM SIGIR Forum, 37(1).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献