Unexpected Recommendation

Unexpected Recommendation is a recommendation approach that belongs to the class of novelty-oriented methods in information retrieval, distinguished by its deliberate generation of recommendations that diverge significantly from users' established preferences or predictable patterns, thereby introducing serendipitous or surprising items not readily anticipated by the user or standard predictive models.

20

Publications

906

Citations

49

Authors

24

Institutions

Publications per year

2017–2026

13

Authors

49

  1. AT
    Alexander Tuzhilin

    New York University, United States

    5 publications · 432 citations

    5

    h-index

  2. DK
    Denis Kotkov

    University of Jyväskylä, Finland

    3 publications · 134 citations

    4

    h-index

  3. PA
    Panagiotis Adamopoulos

    New York University, United States

    3 publications · 369 citations

    3

    h-index

  4. XN
    Xi Niu

    University of North Carolina at Charlotte, United States

    2 publications · 35 citations

    2

    h-index

  5. JV
    Jari Veijalainen

    University of Jyväskylä, Finland

    2 publications · 109 citations

    2

    h-index

1–5 of 49

Venues

  1. ACM Transactions on Intelligent Systems and Technology

    TIST · 2 publications · 244 citations

    2

    h-index

  2. 1

    h-index

  3. The Faculty Digital Archive (New York University)

    Repository · 1 publications · 64 citations

    1

    h-index

  4. Electronics

    1 publications · 39 citations

    1

    h-index

  5. Business Horizons

    1 publications · 19 citations

    1

    h-index

1–5