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

Authors

580

  1. RG
    Ralph Grishman

    New York University, United States

    6 publications · 379 citations

    6

    h-index

  2. FC
    Fabio Ciravegna

    University of Sheffield, United Kingdom

    5 publications · 158 citations

    5

    h-index

  3. WL
    Wai Lam

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 97 citations

    4

    h-index

  4. OE
    Oren Etzioni

    University of Washington, United States

    4 publications · 1.3K citations

    4

    h-index

  5. RY
    Roman Yangarber

    University of Helsinki, Finland

    4 publications · 300 citations

    4

    h-index

1–5 of 580

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 427 citations

    4

    h-index

  2. Knowledge-Based Systems

    4 publications · 98 citations

    4

    h-index

  3. 3

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 254 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 219 citations

    3

    h-index

1–5