Iterative Voting under Uncertainty for Group Recommender Systems (Research Abstract)

  • Lihi Naamani-Dery

    Research output: Contribution to conferencePaperpeer-review

    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”.

    Original languageEnglish
    Pages2400-2401
    Number of pages2
    DOIs
    StatePublished - 1 Jan 2012
    Event26th AAAI Conference on Artificial Intelligence, AAAI 2012 - Toronto, Canada
    Duration: 22 Jul 201226 Jul 2012

    Conference

    Conference26th AAAI Conference on Artificial Intelligence, AAAI 2012
    Country/TerritoryCanada
    CityToronto
    Period22/07/1226/07/12

    ASJC Scopus subject areas

    • Artificial Intelligence

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