Serendipity

Serendipity is a measure in the evaluation of recommender systems that captures the extent to which recommended items are both unexpected and positively surprising to the user, distinguishing it from mere novelty or relevance by incorporating user perception of beneficial unpredictability.

266

Publications

13.9K

Citations

538

Authors

303

Institutions

Publications per year

2017–2026

93

Authors

538

  1. SM
    Stephann Makri

    City, University of London, United Kingdom

    9 publications · 458 citations

    9

    h-index

  2. DK
    Denis Kotkov

    University of Jyväskylä, Finland

    7 publications · 642 citations

    7

    h-index

  3. LM
    Lori McCay‐Peet

    Dalhousie University, Canada

    6 publications · 349 citations

    6

    h-index

  4. EG
    Elaine G. Toms

    Dalhousie University, Canada

    6 publications · 354 citations

    6

    h-index

  5. LB
    L. Beirão da Veiga

    University of Milan, Italy

    5 publications · 167 citations

    5

    h-index

1–5 of 538

Venues

  1. 6

    h-index

  2. Journal of Documentation

    5 publications · 317 citations

    5

    h-index

  3. Communications in Numerical Methods in Engineering

    CNME · 5 publications · 62 citations

    5

    h-index

  4. 5

    h-index

  5. 4

    h-index

1–5