  We consider the challenge of preference elicitation in systems that help
users discover the most desirable item(s) within a given database. Past work on
preference elicitation focused on structured models that provide a factored
representation of users' preferences. Such models require less information to
construct and support efficient reasoning algorithms. This paper makes two
substantial contributions to this area: (1) Strong representation theorems for
factored value functions. (2) A methodology that utilizes our representation
results to address the problem of optimal item selection.
