User Trust Evaluation
User Trust Evaluation is a methodological framework within the field of recommendation systems that assesses the degree to which users perceive a recommender system as reliable, credible, and intentioned toward their best interests based on observable behaviors, system characteristics, and contextual interactions.
296
Publications
14.9K
Citations
913
Authors
377
Institutions
Publications per year
2017–2026
131
Parents
296
DARPA's Explainable Artificial Intelligence Program
David Gunning, David W. Aha · AI Magazine · 2019 · 1.2K citations · Full text
Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making
Carrie J. Cai, Emily Reif, Narayan Hegde et al. · 2019 · 385 citations · Full text
1–5 of 296
913
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377

Macquarie University
Sydney, Australia
14 h-index
33 publications
1.9K citations

Xidian University
Xi'an, China
11 h-index
23 publications
1.7K citations

Beijing University of Posts and Telecommunications
Beijing, China
10 h-index
38 publications
997 citations
Aalto University
Espoo, Finland
10 h-index
13 publications
425 citations

Commonwealth Scientific and Industrial Research Organisation
Canberra, Australia
7 h-index
17 publications
1K citations

Central South University
Changsha, China
5 h-index
7 publications
573 citations
University of Technology Sydney
Sydney, Australia
5 h-index
7 publications
274 citations
University of Maryland, College Park
College Park, United States
4 h-index
9 publications
149 citations
1–8 of 377
8 publications · 263 citations
8
h-index
5 publications · 199 citations
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Repository · 4 publications · 119 citations
4
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4 publications · 131 citations
4
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4 publications · 234 citations
4
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1–5