Localizing users and items from paired comparisons

Suppose that we wish to determine an embedding of points given only paired comparisons of the form “user x prefers item q i null to item q j .” Such observations arise in a variety of contexts, including applications such as recommendation systems, targeted advertisement, and psychological studies. In this paper we first present an optimization-based framework for localizing new users and items when an existing embedding is known. We demonstrate...