User-centric Explanations
User-Centric Explanations is a type of explanation framework in explainable recommendation that prioritizes the user's perspective by tailoring explanations to individual users' preferences, cognitive processes, and decision-making needs, thereby enhancing interpretability, trust, and satisfaction through personalized, meaningful, and actionable reasoning.
41
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1.7K
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163
Authors
62
Institutions
Publications per year
2017–2026
39
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41
Jonathan Dodge, Q. Vera Liao, Yunfeng Zhang et al. · 2019 · 252 citations · Full text
How do visual explanations foster end users' appropriate trust in machine learning?
Fumeng Yang, Zhuanyi Huang, Jean Scholtz et al. · 2020 · 182 citations
Human-Centric Justification of Machine Learning Predictions
Or Biran, Kathleen McKeown · 2017 · 81 citations · Full text
Doha Kim, Yeosol Song, Songyie Kim et al. · Technological Forecasting and Social Change · 2023 · 71 citations
Business, Marketing, Psychology +15
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University of Bologna
Bologna, Italy
2 h-index
4 publications
102 citations

University of Duisburg-Essen
Essen, Germany
2 h-index
13 publications
351 citations
University of Oxford
Oxford, United Kingdom
2 h-index
5 publications
177 citations

Pacific Northwest National Laboratory
Richland, United States
2 h-index
4 publications
564 citations

Technische Universität Darmstadt
Darmstadt, Germany
2 h-index
8 publications
180 citations
Oregon State University
Corvallis, United States
2 h-index
2 publications
275 citations
Michigan Technological University
Houghton, United States
1 h-index
2 publications
120 citations
Heraeus (Germany)
Hanau, Germany
1 h-index
1 publications
25 citations
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Repository · 5 publications · 126 citations
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TIIS · 3 publications · 111 citations
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Conference · 2 publications · 42 citations
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1 publications · 34 citations
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1 publications · 21 citations
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