Sankar Basu
Journal of the Franklin Institute
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.
Sankar Basu
Journal of the Franklin Institute
Nimrod Megiddo
Journal of Symbolic Computation
Tong Zhang, G.H. Golub, et al.
Linear Algebra and Its Applications
A. Gupta, R. Gross, et al.
SPIE Advances in Semiconductors and Superconductors 1990