Cold-start Problem

The Cold-Start Problem is a challenge in collaborative filtering and information filtering systems wherein the system cannot generate accurate recommendations for new users, items, or contexts due to the absence of sufficient historical interaction data.

814

Publications

47.6K

Citations

2.5K

Authors

746

Institutions

Publications per year

2017–2026

521

Authors

2.5K

  1. HY
    Hongzhi Yin

    The University of Queensland, Australia

    6 publications · 587 citations

    7

    h-index

  2. XH
    Xiangnan He

    University of Science and Technology of China, China

    6 publications · 546 citations

    6

    h-index

  3. ME
    Martin Ester

    Simon Fraser University, Canada

    6 publications · 2.7K citations

    6

    h-index

  4. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    6 publications · 320 citations

    6

    h-index

  5. SK
    Sang‐Wook Kim

    Hanyang University, South Korea

    6 publications · 123 citations

    6

    h-index

1–5 of 2.5K

Venues

  1. IEEE Access

    28 publications · 848 citations

    18

    h-index

  2. arXiv (Cornell University)

    Repository · 29 publications · 725 citations

    18

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 18 publications · 1.3K citations

    16

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 17 publications · 2K citations

    15

    h-index

  5. Expert Systems with Applications

    12 publications · 1.3K citations

    12

    h-index

1–5