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
Juliann Opitz, Robert D. Allen, et al.
Microlithography 1998
F.M. Schellenberg, M. Levenson, et al.
BACUS Symposium on Photomask Technology and Management 1991
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence