Recommendation Interfaces

Recommendation Interfaces is a type of human-computer interface that integrates algorithmic suggestions into the analytical workflow to guide users in data exploration, interpretation, or decision-making by filtering, ranking, or highlighting relevant information based on inferred user needs or behavior.

171

Publications

21K

Citations

475

Authors

204

Institutions

Publications per year

2017–2026

69

Authors

475

  1. AF
    Alexander Felfernig

    Graz University of Technology, Austria

    7 publications · 166 citations

    7

    h-index

  2. KV
    Katrien Verbert

    KU Leuven, Belgium

    7 publications · 438 citations

    7

    h-index

  3. PP
    Pearl Pu

    École Polytechnique Fédérale de Lausanne, Switzerland

    5 publications · 160 citations

    5

    h-index

  4. JA
    Joseph A. Konstan

    University of Minnesota, United States

    5 publications · 2K citations

    5

    h-index

  5. LC
    Li Chen

    Hong Kong Baptist University, Hong Kong SAR China

    5 publications · 173 citations

    5

    h-index

1–5 of 475

Venues

  1. Procedia Computer Science

    5 publications · 184 citations

    5

    h-index

  2. User Modeling and User-Adapted Interaction

    4 publications · 94 citations

    4

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 10.3K citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 69 citations

    3

    h-index

  5. IEEE Access

    2 publications · 62 citations

    2

    h-index

1–5