Bm25 Variant Models

BM25 Variant Models is a probabilistic information retrieval framework that extends the original BM25 ranking function by modifying its parameters, normalization strategies, or term weighting schemes to improve document ranking performance under specific retrieval conditions.

16

Publications

4K

Citations

47

Authors

23

Institutions

Publications per year

2017–2026

5

Authors

47

  1. HZ
    Hugo Zaragoza

    Yahoo (Spain), Spain

    3 publications · 3.6K citations

    3

    h-index

  2. SR
    Stephen Robertson

    Microsoft Research (United Kingdom), United Kingdom

    3 publications · 3.6K citations

    3

    h-index

  3. JR
    José R. Pérez-Agüera

    Universidad Complutense de Madrid, Spain

    2 publications · 148 citations

    2

    h-index

  4. VF
    Víctor Fresno

    Universidad Nacional de Educación a Distancia, Spain

    2 publications · 148 citations

    2

    h-index

  5. JX
    Jimmy Xiangji Huang

    York University, Canada

    2 publications · 33 citations

    2

    h-index

1–5 of 47

Venues

  1. Text REtrieval Conference

    Conference · 1 publications · 44 citations

    1

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  2. 1

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  3. 1

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  4. 1

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  5. ArXiv.org

    Repository · 1 publications · 71 citations

    1

    h-index

1–5