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

Authors

45.5K

  1. RG
    Ralph Grishman

    New York University, United States

    83 publications · 9.1K citations

    43

    h-index

  2. JT
    Jun’ichi Tsujii

    The University of Tokyo, Japan

    79 publications · 5.6K citations

    42

    h-index

  3. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    94 publications · 6.7K citations

    42

    h-index

  4. AM
    Andrew McCallum

    University of Massachusetts Amherst, United States

    65 publications · 10.1K citations

    42

    h-index

  5. SA
    Sophia Ananiadou

    University of Manchester, United Kingdom

    91 publications · 5.4K citations

    42

    h-index

1–5 of 45.5K

Venues

  1. arXiv (Cornell University)

    Repository · 775 publications · 32.1K citations

    76

    h-index

  2. Bioinformatics

    167 publications · 22.9K citations

    72

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 244 publications · 22K citations

    68

    h-index

  4. Journal of the American Medical Informatics Association

    JAMIA · 173 publications · 17.4K citations

    67

    h-index

  5. BMC Bioinformatics

    239 publications · 14.7K citations

    64

    h-index

1–5