Generic Summarization

Generic Summarization is a text summarization approach that produces condensed representations of source content without being tailored to a specific domain, purpose, or user context, distinguishing itself from specialized or task-oriented summarization methods by its broad applicability and content-agnostic processing.

88

Publications

6.3K

Citations

200

Authors

88

Institutions

Publications per year

2017–2026

20

Authors

200

  1. RM
    Ramiz M. Aliguliyev

    Azerbaijan National Academy of Sciences, Azerbaijan

    7 publications · 310 citations

    7

    h-index

  2. WL
    Wenjie Li

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 264 citations

    5

    h-index

  3. FW
    Furu Wei

    Microsoft Research Asia (China), China

    4 publications · 220 citations

    4

    h-index

  4. RM
    Rasim M. Аlguliev

    Azerbaijan National Academy of Sciences, Azerbaijan

    4 publications · 169 citations

    4

    h-index

  5. CL
    Chin-Yew Lin

    Microsoft Research Asia (China), China

    4 publications · 285 citations

    4

    h-index

1–5 of 200

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 357 citations

    5

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 126 citations

    3

    h-index

  3. Computational Intelligence

    3 publications · 94 citations

    3

    h-index

  4. Multimedia Tools and Applications

    2 publications · 43 citations

    2

    h-index

  5. IEEE Access

    2 publications · 44 citations

    2

    h-index

1–5