Relevance Diversity

Relevance Diversity is a recommendation system evaluation criterion that balances the inclusion of items satisfying diverse user needs or subtopics within a query’s relevant results, distinguishing itself from pure relevance ranking by explicitly promoting coverage of distinct, pertinent aspects of the information need.

19

Publications

1.9K

Citations

58

Authors

24

Institutions

Publications per year

2017–2026

5

Authors

58

  1. WN
    Wolfgang Nejdl

    L3S Research Center, Germany

    2 publications · 41 citations

    2

    h-index

  2. SV
    Saúl Vargas

    Universidad Autónoma de Madrid, Spain

    2 publications · 820 citations

    2

    h-index

  3. JX
    Jeffery Xu Yu

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 52 citations

    2

    h-index

  4. LC
    Laming Chen

    Tsinghua University, China

    2 publications · 144 citations

    2

    h-index

  5. RS
    Ruihua Song

    Microsoft Research Asia (China), China

    2 publications · 94 citations

    2

    h-index

1–5 of 58

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 144 citations

    2

    h-index

  2. Information Retrieval

    1 publications · 22 citations

    1

    h-index

  3. Biblos-e Archivo (Universidad Autónoma de Madrid)

    Repository · 1 publications · 121 citations

    1

    h-index

  4. Applied Soft Computing

    1 publications · 12 citations

    1

    h-index

  5. International Joint Conference on Natural Language Processing

    Conference · 1 publications · 13 citations

    1

    h-index

1–5