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

Lihi Naamani-Dery

doi:10.1609/aaai.v26i1.8185

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

Lihi Naamani-Dery

Department of Software and Information Systems Engineering

Ben-Gurion University of the Negev

Research output: Contribution to conference › Paper › peer-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 language	American English
Pages	2400-2401
Number of pages	2
DOIs	https://doi.org/10.1609/aaai.v26i1.8185
State	Published - 1 Jan 2012
Event	26th AAAI Conference on Artificial Intelligence, AAAI 2012 - Toronto, Canada Duration: 22 Jul 2012 → 26 Jul 2012

Conference

Conference	26th AAAI Conference on Artificial Intelligence, AAAI 2012
Country/Territory	Canada
City	Toronto
Period	22/07/12 → 26/07/12

All Science Journal Classification (ASJC) codes

Artificial Intelligence

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10.1609/aaai.v26i1.8185

Cite this

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title = "Iterative Voting under Uncertainty for Group Recommender Systems (Research Abstract)",

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”.",

author = "Lihi Naamani-Dery",

note = "Publisher Copyright: Copyright {\textcopyright} 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 26th AAAI Conference on Artificial Intelligence, AAAI 2012 ; Conference date: 22-07-2012 Through 26-07-2012",

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

Abstract

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All Science Journal Classification (ASJC) codes

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