3John S. Breese, David Heckerman, Car Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the 14th Conf. on UAI-98,pp. 43 -52, San Francisco, July 24 -26 1998.
4K. Yu, Z. Wen, X. Xu and M. Ester. Feature Weighting and Instance Selection for Collaborative Filtering.2nd International Workshop on Management of Information on the Web, in conjunction with the 12th International Conference on DEXA' 2001, Munich,Gerneny, 2001.
5Kai Yu, Xiaowei Xu, Jianhua Tao, Martin Ester and Hans -Peter Kriegel. Instance selection techniques for memory - based collaborative filtering. In Proceedings of the second international conf. On data mining, part I visualization and applications,2002.
6Maes, P. Agents that reduce work and information overload.Communications of the ACM, 1994,37:31 - 40.
7Angela Edmunds, Anne Morris. The problem of information overload in business organisations: a review of the lilerature. International Journal of Information Management, 2000,20 : 17 - 28.
8D.R. Tauritz , J.N. Kok, I.G. Sprinkhuizen-Kuyper. Adaptive information filtering using evolutionary computation. Information Sciences, 2000, 122:121-140.
9Funakoshi, Kaname; Ohguro, Takeshi. Content-based collaborative recommender system with detailed use of evaluations. In:KES 4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies (KES'2000), Aug 30-Sep 1, 2000, 253 - 256.
10Belkin,N. J., Croft, W. B.. Information filtering and information retrieval: two sides of the same coin? Communications of the ACM,1992, 35(12) :29 - 38.