Rank Elicitation
Rank Elicitation is a methodological approach within expert elicitation that systematically determines the relative order of variables, outcomes, or hypotheses based on expert judgment, distinguishing itself by focusing on ordinal prioritization rather than quantitative probability assessment.
48
Publications
3.6K
Citations
134
Authors
83
Institutions
Publications per year
2017–2026
6
Parents
48
Estimation of Variance Using Judgment Ordered Ranked Set Samples
S. Lynne Stokes · Biometrics · 1980 · 209 citations
Bayesian inference for Plackett-Luce ranking models
John Guiver, Edward Snelson · 2009 · 171 citations
1–5 of 48
134
MTA-SZTE Research Group on Artificial Intelligence, Hungary
3 publications · 101 citations
3
h-index
2
h-index
2
h-index
2
h-index
MTA-SZTE Research Group on Artificial Intelligence, Hungary
2 publications · 55 citations
2
h-index
1–5 of 134
83

Paderborn University
Paderborn, Germany
3 h-index
5 publications
193 citations
Institut Superieur de Gestion
Paris, France
2 h-index
2 publications
54 citations

Delft University of Technology
Delft, The Netherlands
2 h-index
5 publications
214 citations

Johns Hopkins University
Baltimore, United States
2 h-index
2 publications
148 citations
MTA-SZTE Research Group on Artificial Intelligence
Szeged, Hungary
2 h-index
3 publications
128 citations
University of Sfax
Sfax, Tunisia
2 h-index
4 publications
108 citations
Statistics Collaborative
Washington D.C., United States
2 h-index
5 publications
108 citations
Université Libre de Bruxelles
Brussels, Belgium
2 h-index
2 publications
54 citations
1–8 of 83
3 publications · 75 citations
3
h-index
2 publications · 54 citations
2
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OR · 2 publications · 24 citations
2
h-index
Repository · 2 publications · 87 citations
2
h-index
1 publications · 64 citations
1
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1–5