Leo Liberti, James Ostrowski
Journal of Global Optimization
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.
Leo Liberti, James Ostrowski
Journal of Global Optimization
Corneliu Constantinescu
SPIE Optical Engineering + Applications 2009
Jaione Tirapu Azpiroz, Alan E. Rosenbluth, et al.
SPIE Photomask Technology + EUV Lithography 2009
M. Tismenetsky
International Journal of Computer Mathematics