Recommendation Explanations

Recommendation Explanations is a scholarly contribution in the field of recommender systems that formally constitutes an interpretable rationale generated to justify, clarify, or justify the output of a recommendation algorithm, thereby distinguishing itself from generic model explanations by being intrinsically tied to user decision-making and system transparency in personalized recommendation contexts.

197

Publications

16.6K

Citations

540

Authors

210

Institutions

Publications per year

2017–2026

147

Authors

540

  1. LC
    Li Chen

    Hong Kong Baptist University, Hong Kong SAR China

    9 publications · 986 citations

    9

    h-index

  2. YZ
    Yongfeng Zhang

    Rutgers, The State University of New Jersey, United States

    8 publications · 1.2K citations

    8

    h-index

  3. HW
    Hongning Wang

    University of Virginia, United States

    5 publications · 274 citations

    5

    h-index

  4. KV
    Katrien Verbert

    KU Leuven, Belgium

    5 publications · 326 citations

    5

    h-index

  5. MG
    Mouadh Guesmi

    University of Duisburg-Essen, Germany

    4 publications · 111 citations

    4

    h-index

1–5 of 540

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 198 citations

    9

    h-index

  2. Information Sciences

    5 publications · 130 citations

    5

    h-index

  3. Knowledge-Based Systems

    5 publications · 396 citations

    5

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 207 citations

    4

    h-index

  5. Proceedings of the ACM Web Conference 2022

    Conference · 4 publications · 83 citations

    4

    h-index

1–5