Information Extraction
Information Extraction is a natural language processing task that identifies and extracts structured information from unstructured text by specifying the types of entities, relations, or events of interest according to a predefined schema.
22.8K
Publications
1.4M
Citations
45.5K
Authors
5.9K
Institutions
Publications per year
2017–2026
8.4K
Variants
Biomedical Event ExtractionBiomedical Relation ExtractionBiomedical Terminology ExtractionIeTemporal Information Extraction
22.8K
Authoritative sources in a hyperlinked environment
Jon Kleinberg · Journal of the ACM · 1999 · 9.1K citations · Full text
An algorithm for suffix stripping
Martin Porter · Program electronic library and information systems · 1980 · 8.1K citations
1–5 of 22.8K
45.5K
43
h-index
42
h-index
42
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42
h-index
42
h-index
1–5 of 45.5K
5.9K
Stanford University
Stanford, United States
84 h-index
754 publications
129.9K citations
Carnegie Mellon University
Pittsburgh, United States
84 h-index
767 publications
97.6K citations
University of Washington
Seattle, United States
83 h-index
643 publications
97.5K citations
Tsinghua University
Beijing, China
77 h-index
940 publications
95.8K citations
Google (United States)
Mountain View, United States
74 h-index
537 publications
56.8K citations
Microsoft (United States)
Redmond, United States
73 h-index
511 publications
59.6K citations

University of Massachusetts Amherst
Amherst Center, United States
73 h-index
444 publications
52.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
72 h-index
806 publications
50.9K citations
1–8 of 5.9K
Repository · 775 publications · 32.1K citations
76
h-index
167 publications · 22.9K citations
72
h-index
Conference · 244 publications · 22K citations
68
h-index
JAMIA · 173 publications · 17.4K citations
67
h-index
239 publications · 14.7K citations
64
h-index
1–5