Unsupervised Information Extraction
Unsupervised Information Extraction is an information extraction paradigm that operates without labeled training data, distinguishing itself by automatically identifying and extracting structured knowledge from unannotated text through inherent data patterns and statistical regularities.
202
Publications
11.6K
Citations
580
Authors
237
Institutions
Publications per year
2017–2026
59
Parents
202
Unsupervised named-entity extraction from the Web: An experimental study
Oren Etzioni, Michael Cafarella, Doug Downey et al. · Artificial Intelligence · 2005 · 1.1K citations
Event Extraction as Machine Reading Comprehension
Jian Liu, Yubo Chen, Kang Liu et al. · 2020 · 303 citations · Full text
1–5 of 202
580
6
h-index
5
h-index
4
h-index
4
h-index
4
h-index
1–5 of 580
237
University of Washington
Seattle, United States
8 h-index
25 publications
9.8K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
7 h-index
16 publications
1.1K citations
New York University
New York, United States
5 h-index
10 publications
802 citations
Google (United States)
Mountain View, United States
5 h-index
10 publications
819 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
8 publications
329 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
7 publications
227 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
10 publications
433 citations
University of Sheffield
Sheffield, United Kingdom
4 h-index
9 publications
195 citations
1–8 of 237
PVLDB · 4 publications · 427 citations
4
h-index
4 publications · 98 citations
4
h-index
3 publications · 240 citations
3
h-index
TKDE · 3 publications · 254 citations
3
h-index
Repository · 3 publications · 219 citations
3
h-index
1–5