Matthew A Grayson
Journal of Complexity
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.
Matthew A Grayson
Journal of Complexity
Ronald Fagin, Ravi Kumar, et al.
SIAM Journal on Discrete Mathematics
Nimrod Megiddo
Journal of Symbolic Computation
Robert Manson Sawko, Malgorzata Zimon
SIAM/ASA JUQ