Query-document Relevance

Query-Document Relevance is a relevance assessment measure that evaluates the degree to which a document satisfies the information need expressed in a query within an information retrieval system.

142

Publications

8.5K

Citations

341

Authors

132

Institutions

Publications per year

2017–2026

34

Authors

341

  1. WB
    W. Bruce Croft

    University of Massachusetts Amherst, United States

    10 publications · 1.4K citations

    10

    h-index

  2. IR
    Ian Ruthven

    University of Strathclyde, United Kingdom

    4 publications · 75 citations

    4

    h-index

  3. NC
    Nick Craswell

    Microsoft (United States), United States

    4 publications · 734 citations

    4

    h-index

  4. RW
    Ryen W. White

    Microsoft (United States), United States

    4 publications · 188 citations

    4

    h-index

  5. PB
    Peter Bruza

    Queensland University of Technology, Australia

    3 publications · 124 citations

    3

    h-index

1–5 of 341

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 266 citations

    7

    h-index

  2. ACM SIGIR Forum

    6 publications · 859 citations

    6

    h-index

  3. Information Processing & Management

    6 publications · 177 citations

    6

    h-index

  4. Journal of the American Society for Information Science

    JASIS · 3 publications · 158 citations

    3

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 132 citations

    2

    h-index

1–5