Mario Blaum, John L. Fan, et al.
IEEE International Symposium on Information Theory - Proceedings
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.
Mario Blaum, John L. Fan, et al.
IEEE International Symposium on Information Theory - Proceedings
R.B. Morris, Y. Tsuji, et al.
International Journal for Numerical Methods in Engineering
David L. Shealy, John A. Hoffnagle
SPIE Optical Engineering + Applications 2007
Laxmi Parida, Pier F. Palamara, et al.
BMC Bioinformatics