TY - JOUR
T1 - Iterative Voting under Uncertainty for Group Recommender Systems (Research Abstract)
AU - Naamani-Dery, Lihi
N1 - Publisher Copyright:
Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2012
Y1 - 2012
N2 - Group Recommendation Systems (GRS's) assist groups when trying to reach a joint decision. I use probabilistic data and apply voting theory to GRS's in order to minimize user interaction and output an approximate or definite “winner item”.
AB - Group Recommendation Systems (GRS's) assist groups when trying to reach a joint decision. I use probabilistic data and apply voting theory to GRS's in order to minimize user interaction and output an approximate or definite “winner item”.
UR - http://www.scopus.com/inward/record.url?scp=85167417399&partnerID=8YFLogxK
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AN - SCOPUS:85167417399
SP - 2400
EP - 2401
JO - Proceedings of the National Conference on Artificial Intelligence
JF - Proceedings of the National Conference on Artificial Intelligence
T2 - 26th AAAI Conference on Artificial Intelligence, AAAI 2012
Y2 - 22 July 2012 through 26 July 2012
ER -