1LAWRENCE R D,ALMAS G S, KOTLYAR V,et al. Personalization of supermarket product recommendations (J ]. Data Mining and Knowledge Discover,/,2001,5 ( 1/2 ) : 11 - 32.
2McLAUGHLIN M R, HERLOCKER J L. A collaborative filtering algo- rithm and evaluation metric that accurately model the user experience [ C]//Proc of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval New York: ACM Press.2004:329-336.
3JAMALI M, ESTER M. Using a trust network to improve top-N recom- mendation[ C]//Proc of the 3rd ACM Conference on Recommender Systems. New York : ACM Press ,2009 : 181-188.
4LI Rui-feng,ZHANG Yin, YU Hai-han, et aL A social network-aware top-N recommender system using GPU[ C]//Proc of ACM/IEEE Joint Conference on Digital Libraries. 2011:287-296.
5ELEFTHERIOS T, YANNIS M. Product recommendation and rating prediction based on multi-modal social networks [ C ]//Proc of the 5 th ACM Conference on Recommender Systems. Now York:ACM Press, 2011:61-68.
6MA Hao,ZHOU Deng-yong, LIU Chao. Recommender systems with so- cial regularization [ C ]//Proc of the 4th ACM International Conference on Web'Search and Data Mining. New York : ACM Press, 2011 : 287- 296.
7ADOMAVICIUS G, TUZHILIN A. Toward the next generation of recommender systems : a survey of the state-of-the-art and possible ex- tensions[ J]. IEEE Trans on Knowledge and Data Engineering, 2005,17(6) :?34-?49.
8SEN S W. Nurturing tagging communities [ D ]. Minnesota:University of Minnesota, 2009.
9JEH G, WIDOM J. SimRank : a measure of structural context similarity [ C ]//Proc of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York iACM Press ,2002:538-543.
10HERLOCKER J L,KONSTAN J A,TERVEEN L G,et al. Evaluating collaborative filtering recommender systems [ J ]. ACM Trans on In- formation Systems ,2004,22 ( 1 ) :5- 53.
