Query Likelihood Model

Query Likelihood Model is a probabilistic retrieval model that ranks documents based on the likelihood of a query being generated from their language model, typically estimated using maximum likelihood or smoothed probability distributions.

36

Publications

2.9K

Citations

92

Authors

41

Institutions

Publications per year

2017–2026

8

Authors

92

  1. WB
    W. Bruce Croft

    University of Massachusetts Amherst, United States

    6 publications · 869 citations

    6

    h-index

  2. RZ
    Ruqing Zhang

    University of Chinese Academy of Sciences, China

    2 publications · 50 citations

    3

    h-index

  3. JG
    Jiafeng Guo

    Chinese Academy of Sciences, China

    2 publications · 50 citations

    3

    h-index

  4. XC
    Xueqi Cheng

    Chinese Academy of Sciences, China

    2 publications · 50 citations

    3

    h-index

  5. YL
    Yingyan Li

    Chinese Academy of Sciences, China

    2 publications · 50 citations

    2

    h-index

1–5 of 92

Venues

  1. ACM Transactions on Information Systems

    3 publications · 1.3K citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 37 citations

    2

    h-index

  3. Information Systems

    1 publications · 38 citations

    1

    h-index

  4. UvA-DARE (University of Amsterdam)

    Repository · 1 publications · 19 citations

    1

    h-index

  5. Journal of Information Science

    JIS · 1 publications · 22 citations

    1

    h-index

1–5