Friday 26 October 2012

[1] Resnick and Varian. Recommender systems.
Communications of the ACM, 40(3):56¨C58, 1997.
[2] Schafer, J. B., Konstan, J. and Riedl, J.: 1999,
‘Recommender Systems in E-Commerce’. In: EC ’99:
Proceedings of the First ACM Conference on Electronic
Commerce, Denver, CO, pp. 158-166.
[3] Pazzani, M. J.: 1999, ‘A Framework for Collaborative,
Content-Based and Demographic Filtering’. Artificial
Intelligence Review, 13 (5/6), 393-408.
[4] Andreas Milda,, Thomas Reutterer, An improved
collaborative filtering approach for prediction gcrosscategory
purchases based on binary market basket data,
Journal of Retailing and Consumer Services, 10 (2003)
123–133
[5] YU Li, LIU Lu, LI Xuefeng, A Hybrid Collaborative
Filtering Method for Multiple-interests and Multiplecontent
Recommendation in E-Commerce, Expert System
with Application, Jan. 2005, Vol.28 P67-P77
[6] YU Li, LIU Lu, Personalized Recommendation in ECommerce
and its Application in China, The Seventh
International Conference on Industrial Management, Oct.
2004, Japan
[7] YU Li, LIU Lu, LI Xuefeng, (2004) Study on Personalized
Recommendation Algorithm for User’s Multiple Interests,
Vol.10 No.12, P1610-P1615 (Chinese)
[8] YU Li, LIU Lu, Collaborative Filtering Algorithm Based
on Mutual Information, The Eighth Pacific Asia
Conference on Information System, Aug. 2004, Shanghai,
China, P274-P287
[9] YU Li, LIU Lu, Matrix view of the smallest association
rule set based on largest frequent item-set, Computer
Engineering and Application, No.23, 2003 (Chinese)
[10] Andreas Mild, Martin Natter, A critical view on
recommendation systems, Working Paper Series ,Vienna
University of Economics and Business

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