Abstract
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”.
Cite
CITATION STYLE
APA
Naamani-Dery, L. (2012). Iterative Voting under Uncertainty for Group Recommender Systems (Research Abstract). In Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012 (pp. 2400–2401). AAAI Press. https://doi.org/10.1609/aaai.v26i1.8185
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