Group Satisfaction Optimization
Group Satisfaction Optimization is a recommendation framework that specifically aims to maximize the collective satisfaction of a group by aggregating individual preferences into a unified decision, distinguishing itself from individual-level recommendation approaches through its focus on joint utility and fairness across group members.
8
Publications
225
Citations
24
Authors
13
Institutions
Publications per year
2017–2026
5
8
Users' satisfaction in recommendation systems for groups
Lucas Carvalho, Hendrik Macedo · 2013 · 51 citations
Qifeng Wan, Xuanhua Xu, Jun Zhuang · Group Decision and Negotiation · 2020 · 49 citations
From Group Recommendations to Group Formation
Senjuti Basu Roy, Laks V. S. Lakshmanan, Rui Liu · 2015 · 48 citations
David Boix‐Cots, Francesc Pardo-Bosch, Pablo Pujadas · Expert Systems with Applications · 2022 · 20 citations · Full text
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University of Washington Tacoma
Tacoma, United States
2 h-index
4 publications
124 citations

University of British Columbia
Vancouver, Canada
2 h-index
2 publications
62 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
1 h-index
3 publications
60 citations

Universidade Federal de Sergipe
Aracaju, Brazil
1 h-index
2 publications
102 citations

Central South University
Changsha, China
1 h-index
3 publications
147 citations

University of Naples Federico II
Naples, Italy
1 h-index
4 publications
76 citations

Beijing Institute of Petrochemical Technology
Beijing, China
1 h-index
1 publications
11 citations
RWTH Aachen University
Aachen, Germany
1 h-index
1 publications
13 citations
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1 publications · 13 citations
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1 publications · 11 citations
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1 publications · 49 citations
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1 publications · 19 citations
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1 publications · 20 citations
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