Image-based Recommendation

Image-Based Recommendation is a content-based recommendation approach that uniquely utilizes visual features extracted from images as the primary basis for generating personalized recommendations.

92

Publications

6.4K

Citations

340

Authors

145

Institutions

Publications per year

2017–2026

52

Authors

340

  1. JL
    Jiebo Luo

    University of Rochester, United States

    5 publications · 253 citations

    5

    h-index

  2. JM
    Julian McAuley

    University of California San Diego, United States

    5 publications · 2.7K citations

    5

    h-index

  3. QT
    Qi Tian

    The University of Texas at San Antonio, United States

    3 publications · 386 citations

    3

    h-index

  4. WK
    Wang-Cheng Kang

    University of California San Diego, United States

    3 publications · 375 citations

    3

    h-index

  5. XJ
    Xin Jin

    University of Illinois Urbana-Champaign, United States

    3 publications · 172 citations

    3

    h-index

1–5 of 340

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 118 citations

    4

    h-index

  2. IEEE Access

    3 publications · 86 citations

    3

    h-index

  3. IEEE Transactions on Multimedia

    3 publications · 134 citations

    3

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 229 citations

    2

    h-index

  5. ACM Transactions on Intelligent Systems and Technology

    TIST · 2 publications · 56 citations

    2

    h-index

1–5