Knowledge Representation Modeling is a systematic framework within knowledge base design that formally structures symbolic or computational representations of knowledge to enable machine interpretability, distinguishable by its focus on ontological commitments, representational primitives, and logical expressiveness in encoding domain-specific knowledge.
1.3K
Publications
83.1K
Citations
2.7K
Authors
923
Institutions
Publications per year
2017–2026
174
Parents
Publications
1.3K
A translation approach to portable ontology specifications
Thomas Gruber · Knowledge Acquisition · 1993 · 12.5K citations
1–5 of 1.3K
Authors
2.7K
- RJ
14
h-index
- YW
10
h-index
- PF
10
h-index
- HJ
10
h-index
- DF
8
h-index
1–5 of 2.7K
Institutions
923
Stanford University
Stanford, United States
21 h-index
37 publications
15.1K citations
The University of Texas at Austin
Austin, United States
15 h-index
32 publications
2.8K citations
University of Calgary
Calgary, Canada
14 h-index
28 publications
1.4K citations
University of Toronto
Toronto, Canada
14 h-index
24 publications
3.8K citations
University of Maryland, College Park
College Park, United States
13 h-index
30 publications
2.3K citations
AT&T (United States)
Bedminster, United States
13 h-index
25 publications
2.6K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
11 h-index
13 publications
3.3K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
16 publications
428 citations
1–8 of 923
Venues
- International Joint Conference on Artificial Intelligence
Conference · 26 publications · 1.3K citations
19
h-index
- IEEE Expert
25 publications · 989 citations
18
h-index
- Artificial Intelligence
26 publications · 2.9K citations
18
h-index
- Knowledge-Based Systems
21 publications · 778 citations
17
h-index
- arXiv (Cornell University)
Repository · 24 publications · 910 citations
16
h-index
1–5