Cross-document Information Extraction

Cross-Document Information Extraction is a type of information extraction that identifies and synthesizes semantic relationships and entities across multiple, distinct documents, distinguishing itself from single-document approaches by leveraging inter-document context to infer implicit or distributed knowledge.

35

Publications

2.6K

Citations

129

Authors

55

Institutions

Publications per year

2017–2026

8

Authors

129

  1. HJ
    Heng Ji

    Rensselaer Polytechnic Institute, United States

    4 publications · 516 citations

    4

    h-index

  2. RG
    Ralph Grishman

    New York University, United States

    3 publications · 464 citations

    3

    h-index

  3. DR
    Dan Roth

    University of Illinois Urbana-Champaign, United States

    2 publications · 66 citations

    2

    h-index

  4. HF
    Hao Fei

    Wuhan University, China

    2 publications · 74 citations

    2

    h-index

  5. DY
    David Yarowsky

    Johns Hopkins University, United States

    2 publications · 57 citations

    2

    h-index

1–5 of 129

Venues

  1. 2

    h-index

  2. Data & Knowledge Engineering

    DKE · 1 publications · 32 citations

    1

    h-index

  3. Applied Soft Computing

    1 publications · 11 citations

    1

    h-index

  4. Information Sciences

    1 publications · 28 citations

    1

    h-index

  5. RECERCAT (Consorci de Serveis Universitaris de Catalunya)

    Repository · 1 publications · 11 citations

    1

    h-index

1–5