Expert Knowledge Extraction
Expert Knowledge Extraction is a scholarly methodological process that systematically identifies, formalizes, and integrates domain-specific insights from recognized subject matter experts into structured representations to support best practice derivation within a given field.
517
Publications
21.4K
Citations
2K
Authors
809
Institutions
Publications per year
2017–2026
185
Parents
517
SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse
Frank Koopmans, Pim van Nierop, Maria Andres‐Alonso et al. · Neuron · 2019 · 1K citations · Full text
The problem of extracting the knowledge of experts
Robert R. Hoffman · AI Magazine · 1987 · 340 citations
A survey of Bayesian Network structure learning
Neville K. Kitson, Anthony C. Constantinou, Zhigao Guo et al. · Artificial Intelligence Review · 2023 · 328 citations · Full text
1–5 of 517
2K
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809
University of Wisconsin–Madison
Madison, United States
7 h-index
15 publications
1.3K citations

Chinese Academy of Sciences
Beijing, China
6 h-index
14 publications
1.5K citations

Universidad de Granada
Granada, Spain
6 h-index
17 publications
390 citations

University of Helsinki
Helsinki, Finland
5 h-index
8 publications
442 citations

University of Amsterdam
Amsterdam, The Netherlands
5 h-index
8 publications
680 citations
University of Arizona
Tucson, United States
4 h-index
11 publications
999 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
8 publications
164 citations

Northwestern Polytechnical University
Xi'an, China
4 h-index
11 publications
320 citations
1–8 of 809
22 publications · 703 citations
16
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Repository · 7 publications · 159 citations
7
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7 publications · 166 citations
7
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6 publications · 368 citations
6
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6 publications · 458 citations
6
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