Abstract
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.
of optimal item selection.
Original language | English |
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Pages | 51-59 |
Number of pages | 9 |
State | Published - 2004 |
Event | 04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence - Banff, Canada Duration: 7 Jul 2004 → 11 Jul 2004 |
Conference
Conference | 04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence |
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Country/Territory | Canada |
City | Banff |
Period | 7/07/04 → 11/07/04 |