3Rashid A M. Mining influence in recommender systems [ D ]. Min- nesota: University of Minnesota, 2007.
4Rich E. User modeling via stereotypes [ J ]. Cognitive Science, 1979, 3(4) :329 -354.
5Goldberg D, Nichols D, Oki B M, et al. Using collaborative filte- ring to weave an information tapestry [ J ]. Communications of the ACM, 1992, 35(12) :61 -70.
6Hill W, Stead L, Rosenstein M, et al. Recommending and evalua- ting choices in a virtual community of use [ C ]//Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Sys- tems. Denver: ACM Press, 1995: 175- 186.
7Shardanand U, Maes P. Social information filtering : Algorithms for automating "word of mouth" [ C ]// Proceedings of ACM CHI' 95 Conference on Human Factors in Computing Systems. Denver: ACM Press, 1995:210 -217.
8Belkin N, Croft B W. Information filtering and information retriev- al: Two sides of the same coin [ J ]. Communication of the ACM, 1992, 35(12): 29-38.
9Schafer J B, Konstan J A, Riedl J. E-commerce recommendation applications [ J ]. Data Mining and Knowledge Discovery, 2001,5 (1) :115 -153.
10Murthi B P S, Sumit Sarkar. The role of the management sciences in research on personalization[ J]. Management Science, 2003,49 (10) : 1344 -1362.
