Persistently Effective Query Selection in Preference Elicitation

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Proceedings titleInternational Conference on Intelligent Agent Technology, 2007. IAT '07. IEEE/WIC/ACM
ConferenceThe 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), November 2-5, 2007., Fremont, California, USA
Pages491497; # of pages: 7
AbstractThe selection of queries that will provide maximum information regarding a user's preferences is a key component of effective preference elicitation. We discuss a technique for selecting a candidate set of comparison queries whose answers will reveal a significant amount of information about the user's preferences. Computationally expensive utility evaluation of queries can then be confined to this set. Furthermore, this set of queries is chosen so that the response to one query does not resolve any other queries in the set, thus eliminating the need to recompute a new candidate set each time. Experiments run on a case with 30 outcomes show that our chosen queries reveal two to three times as many preferences as random selection, and asking our persistent set of queries reveals 10-12% more preferences than the best n individual queries.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number49846
NPARC number8913433
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Record identifier69219614-d3c7-46d8-a68f-af35e3416b55
Record created2009-04-22
Record modified2016-05-09
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