Error Classification
Error Classification is a systematic framework in the field of Error Analysis that categorizes linguistic or computational errors based on their underlying causes, types, or manifestations, distinguishing it from other analytical methods by its focus on organizing errors into structured typologies for diagnostic or corrective purposes.
253
Publications
13K
Citations
721
Authors
355
Institutions
Publications per year
2017–2026
47
Parents
253
1–5 of 253
721
3
h-index
3
h-index
University of Illinois Urbana-Champaign, United States
3 publications · 302 citations
3
h-index
3
h-index
2
h-index
1–5 of 721
355
NTT (Japan)
Tokyo, Japan
4 h-index
8 publications
155 citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
4 h-index
5 publications
186 citations
Inje University
Gimhae, South Korea
3 h-index
5 publications
108 citations
University of New Brunswick
Fredericton, Canada
3 h-index
9 publications
1.5K citations
University of Florida
Gainesville, United States
3 h-index
13 publications
679 citations

Universidade Estadual de Campinas (UNICAMP)
Campinas, Brazil
3 h-index
4 publications
180 citations
Intel (United States)
Santa Clara, United States
3 h-index
9 publications
300 citations
Stanford University
Stanford, United States
3 h-index
3 publications
143 citations
1–8 of 355
Repository · 5 publications · 133 citations
5
h-index
Repository · 4 publications · 270 citations
4
h-index
4 publications · 149 citations
4
h-index
3 publications · 69 citations
3
h-index
2 publications · 125 citations
2
h-index
1–5