Domain Knowledge Integration
Domain Knowledge Integration is the systematic incorporation of domain-specific insights, principles, or constraints into the design or adaptation of computational models, distinguishing it from general or domain-agnostic feature engineering approaches.
1.4K
Publications
75.7K
Citations
5.1K
Authors
1.4K
Institutions
Publications per year
2017–2026
596
1.4K
Neural Architectures for Named Entity Recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian et al. · 2016 · 4.4K citations · Full text
Explainable Machine Learning for Scientific Insights and Discoveries
Ribana Roscher, Bastian Bohn, Marco F. Duarte et al. · IEEE Access · 2020 · 973 citations · Full text
1–5 of 1.4K
5.1K
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1.4K
Carnegie Mellon University
Pittsburgh, United States
21 h-index
75 publications
25.4K citations
Stanford University
Stanford, United States
19 h-index
45 publications
5.3K citations

Centre National de la Recherche Scientifique
Paris, France
18 h-index
48 publications
1.7K citations
Massachusetts Institute of Technology
Cambridge, United States
17 h-index
36 publications
1.6K citations
Tsinghua University
Beijing, China
17 h-index
73 publications
5.8K citations

Harbin Institute of Technology
Harbin, China
15 h-index
56 publications
2K citations

Chinese Academy of Sciences
Beijing, China
15 h-index
51 publications
2.8K citations
University of Michigan
Ann Arbor, United States
14 h-index
37 publications
1.1K citations
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Repository · 40 publications · 1.4K citations
21
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18 publications · 1.5K citations
15
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13 publications · 681 citations
13
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Conference · 13 publications · 437 citations
12
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Repository · 11 publications · 212 citations
10
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