Topic Selection Description (excerpt from CSC
691B, slightly edited)
Topic: Artificial intelligence: Preference elicitation
Description: This research investigates methods for querying a
user about their preferences
over an outcome space, in order to elicit the preference structure they
have over attributes of possible outcomes.
Motivation: The preference elicitation problem has received
considerable attention in recent years with the advance of the Internet.
Its growing importance is due to its many applications in e-commerce and
environmental resource management, to promote the development of
personalized services for users and the selection of the top of a set
of alternatives.
References:
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Craig Boutilier, Ronen Brafman, Chris Geib, and David Poole, "A constraint-based
approach to preference elicitation and decision making," AAAI Spring Symposium
on Qualitative Decision Theory, 1997. [Boutilier is one of the
most published researchers in the area; this seems like a nice approach
to the general problem, and should have some good references to follow.]
-
Craig Boutilier, Fahiem Bacchus, and Ronen I. Brafman, "UCP-Networks: A
directed graphical representation of conditional utilities," UAI 2001,
pp. 56--64. [Not about preference elicitation per se, but
about representing structured utilities, which can help to guide the elicitation
process.]
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Fahiem Bacchus and Adam J. Grove. "Utility independence in a qualitative
decision theory," Proceedings of KR'96, pages 542--552, 1996. [Everybody
seems to cite this paper.]
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Cohen, Shapire, and Singer, Learning to Order Things, JAIR 10:243-270,
1999. [Not exactly elicitation of a full preference function, but a
related problem of learning rank-ordering functions over sets of objects.]