Query-focused Summarization

Query-Focused Summarization is a type of text summarization that generates a concise summary tailored to a specific user query by selecting and emphasizing content from the source documents that is most relevant to the given query.

148

Publications

7K

Citations

359

Authors

162

Institutions

Publications per year

2017–2026

48

Authors

359

  1. WL
    Wenjie Li

    Hong Kong Polytechnic University, Hong Kong SAR China

    11 publications · 596 citations

    11

    h-index

  2. FW
    Furu Wei

    Microsoft Research Asia (China), China

    8 publications · 367 citations

    8

    h-index

  3. SL
    Sujian Li

    Peking University, China

    6 publications · 364 citations

    6

    h-index

  4. IR
    Ian Ruthven

    University of Strathclyde, United Kingdom

    4 publications · 186 citations

    4

    h-index

  5. JM
    Joemon M. Jose

    University of Glasgow, United Kingdom

    4 publications · 186 citations

    4

    h-index

1–5 of 359

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 478 citations

    10

    h-index

  2. Information Sciences

    4 publications · 149 citations

    4

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 153 citations

    4

    h-index

  4. Information Processing & Management

    4 publications · 402 citations

    4

    h-index

  5. Expert Systems with Applications

    4 publications · 199 citations

    4

    h-index

1–5