Relevance Assessment

Relevance Assessment is a methodological process in information retrieval evaluation that determines the degree to which retrieved documents satisfy the informational needs expressed in a query, distinguished by its reliance on human or automated judgments to classify document-query pairs as relevant or non-relevant.

842

Publications

60K

Citations

1.8K

Authors

725

Institutions

Publications per year

2017–2026

152

Authors

1.8K

  1. SR
    Stephen Robertson

    Microsoft Research (United Kingdom), United Kingdom

    15 publications · 4.1K citations

    15

    h-index

  2. SM
    Stefano Mizzaro

    University of Udine, Italy

    13 publications · 1.3K citations

    13

    h-index

  3. JA
    James Allan

    University of Massachusetts Amherst, United States

    11 publications · 798 citations

    11

    h-index

  4. WB
    W. Bruce Croft

    University of Massachusetts Amherst, United States

    11 publications · 878 citations

    11

    h-index

  5. FS
    Falk Scholer

    RMIT University, Australia

    9 publications · 537 citations

    9

    h-index

1–5 of 1.8K

Venues

  1. Journal of the American Society for Information Science

    JASIS · 38 publications · 5.9K citations

    31

    h-index

  2. 24

    h-index

  3. Information Processing & Management

    29 publications · 2.6K citations

    20

    h-index

  4. Journal of Documentation

    22 publications · 2.5K citations

    17

    h-index

  5. ACM SIGIR Forum

    11 publications · 2K citations

    11

    h-index

1–5