Indicative Summarization

Indicative Summarization is a type of text summarization that belongs to the class of summarization methods designed to convey the scope, purpose, and structure of a source document without reproducing its content verbatim, thereby distinguishing itself from informative or extractive approaches by focusing on conceptual representation rather than detailed subject matter.

22

Publications

890

Citations

38

Authors

25

Institutions

Publications per year

2017–2026

4

Authors

38

  1. MK
    Min‐Yen Kan

    National University of Singapore, Singapore

    5 publications · 173 citations

    5

    h-index

  2. HS
    Horacio Saggion

    Universitat Pompeu Fabra, Spain

    4 publications · 222 citations

    4

    h-index

  3. GL
    Guy Lapalme

    Université de Montréal, Canada

    4 publications · 222 citations

    4

    h-index

  4. KM
    Kathleen McKeown

    Columbia University, United States

    4 publications · 150 citations

    4

    h-index

  5. JL
    Judith L. Klavans

    Columbia University, United States

    3 publications · 128 citations

    3

    h-index

1–5 of 38

Venues

  1. Computational Linguistics

    1 publications · 140 citations

    1

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 103 citations

    1

    h-index

  3. Journal of the American Society for Information Science

    JASIS · 1 publications · 86 citations

    1

    h-index

  4. Journal of Computer Science

    1 publications · 58 citations

    1

    h-index

  5. ACM Transactions on Information Systems

    1 publications · 58 citations

    1

    h-index

1–5