Joy Y. Cheng, Daniel P. Sanders, et al.
SPIE Advanced Lithography 2008
A recommendation system tracks past actions of a group of users to make recommendations to individual members of the group. The growth of computer-mediated marketing and commerce has led to increased interest in such systems. We introduce a simple analytical framework for recommendation systems, including a basis for defining the utility of such a system. We perform probabilistic analyses of algorithms within this framework. These analyses yield insights into how much utility can be derived from knowledge of past user actions.
Joy Y. Cheng, Daniel P. Sanders, et al.
SPIE Advanced Lithography 2008
Zhengxin Zhang, Ziv Goldfeld, et al.
Foundations of Computational Mathematics
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering
Guillaume Buthmann, Tomoya Sakai, et al.
ICASSP 2025