Explanation Satisfaction
Explanation Satisfaction is a user-centered evaluation metric in explainable recommendation systems that quantifies the extent to which generated explanations meet users' cognitive and informational needs in justifying personalized recommendations.
33
Publications
3.1K
Citations
87
Authors
44
Institutions
Publications per year
2017–2026
26
Parents
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Explainable Recommendation a survey and new perspectives
2020 · 716 citations
Explaining Recommendations: Satisfaction vs. Promotion
Mustafa Bilgic, Raymond J. Mooney · 2005 · 253 citations
Explainable Reinforcement Learning Through a Causal Lens
2021 · 250 citations · Full text
Metrics for Explainable AI: Challenges and Prospects
Robert R. Hoffman, Shane T. Mueller, Gary Klein et al. · arXiv (Cornell University) · 2018 · 220 citations · Full text
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44

University of Duisburg-Essen
Essen, Germany
3 h-index
13 publications
284 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
4 publications
174 citations

Sorbonne Université
Paris, France
2 h-index
4 publications
174 citations
Graz University of Technology
Graz, Austria
2 h-index
8 publications
445 citations
Michigan Technological University
Houghton, United States
2 h-index
3 publications
368 citations
AXA (France)
Paris, France
2 h-index
3 publications
156 citations

The University of Melbourne
Melbourne, Australia
2 h-index
5 publications
482 citations
Sungkyunkwan University
Seoul, South Korea
2 h-index
6 publications
426 citations
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Repository · 2 publications · 238 citations
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Conference · 1 publications · 15 citations
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1 publications · 13 citations
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1 publications · 33 citations
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Conference · 1 publications · 75 citations
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