Derivation Rules
Derivation Rules is a type of business rule that specifies how a data element or fact is logically inferred or computed from other explicitly known data elements or facts within a formal knowledge or information system.
149
Publications
5.8K
Citations
279
Authors
160
Institutions
Publications per year
2017–2026
19
Parents
149
Scalable inference and training of context-rich syntactic translation models
Michel Galley, Jonathan Graehl, Kevin Knight et al. · 2006 · 419 citations · Full text
Segmentation of building facades using procedural shape priors
Olivier Teboul, Loïc Simon, Panagiotis Koutsourakis et al. · 2010 · 186 citations
Foundations of computer science
Viera K. Proulx, Richard Rasala, Harriet Fell · ACM SIGCSE Bulletin · 1996 · 161 citations · Full text
1–5 of 149
279
3
h-index
Brandenburg University of Technology Cottbus-Senftenberg, Germany
3 publications · 94 citations
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 279
160
Stanford University
Stanford, United States
4 h-index
5 publications
154 citations
University of Southern California
Los Angeles, United States
4 h-index
8 publications
2.3K citations
Eindhoven University of Technology
Eindhoven, The Netherlands
3 h-index
3 publications
91 citations

Hokkaido University
Sapporo, Japan
3 h-index
5 publications
120 citations
UCLouvain
Louvain-la-Neuve, Belgium
3 h-index
7 publications
512 citations
University of Luxembourg
Luxembourg, Luxembourg
3 h-index
4 publications
98 citations

Nanjing University of Aeronautics and Astronautics
Nanjing, China
2 h-index
4 publications
236 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
6 publications
204 citations
1–8 of 160
PROC · 3 publications · 152 citations
3
h-index
3 publications · 78 citations
3
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3 publications · 71 citations
3
h-index
2 publications · 43 citations
2
h-index
Repository · 2 publications · 37 citations
2
h-index
1–5