User Preference Modeling

User Preference Modeling is a computational framework that formalizes the acquisition, representation, and adaptation of individual or collective user preferences within recommendation systems by integrating behavioral, contextual, and multi-criteria data to enable personalized and group-aware adaptive user interfaces.

1.8K

Publications

96.2K

Citations

5K

Authors

1.2K

Institutions

Publications per year

2017–2026

784

Authors

5K

  1. XH
    Xiangnan He

    University of Science and Technology of China, China

    24 publications · 2.2K citations

    20

    h-index

  2. TC
    Tat‐Seng Chua

    National University of Singapore, Singapore

    21 publications · 2.2K citations

    18

    h-index

  3. FR
    Francesco Ricci⋆

    Free University of Bozen-Bolzano, Italy

    22 publications · 1.1K citations

    16

    h-index

  4. LN
    Liqiang Nie

    Shandong University, China

    15 publications · 1.4K citations

    14

    h-index

  5. XW
    Xiang Wang

    National University of Singapore, Singapore

    12 publications · 976 citations

    12

    h-index

1–5 of 5K

Venues

  1. Expert Systems with Applications

    43 publications · 2.4K citations

    28

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 32 publications · 2.3K citations

    23

    h-index

  3. ACM Transactions on Information Systems

    27 publications · 2.8K citations

    22

    h-index

  4. IEEE Access

    28 publications · 919 citations

    19

    h-index

  5. arXiv (Cornell University)

    Repository · 33 publications · 1.4K citations

    18

    h-index

1–5