Concepedia

Implicit Feedback Learning

Implicit Feedback Learning is a machine learning approach within online recommendation systems that infers user preferences from observable user behaviors—such as clicks, dwell times, or purchase histories—without relying on explicit ratings or direct feedback, thereby distinguishing itself from methods based on explicitly provided user judgments.

91

Publications

13.4K

Citations

307

Authors

133

Institutions

Publications per year

2017–2026

55

Parents

Publications

91

Neural Collaborative Filtering

Xiangnan He, Lizi Liao, Hanwang Zhang et al. · 2017 · 6.6K citations · Full text

, , +15

Fast Matrix Factorization for Online Recommendation with Implicit Feedback

Xiangnan He, Hanwang Zhang, Min‐Yen Kan et al. · 2016 · 1K citations

, , +11

Unbiased Learning-to-Rank with Biased Feedback

Thorsten Joachims, Adith Swaminathan, Tobias Schnabel · 2017 · 514 citations · Full text

, , +12

Top-K Off-Policy Correction for a REINFORCE Recommender System

Minmin Chen, Alex Beutel, Paul Covington et al. · 2019 · 386 citations

, , +15

Improving pairwise learning for item recommendation from implicit feedback

Steffen Rendle, Christoph Freudenthaler · 2014 · 382 citations

, , +10

1–5 of 91

Authors

307

  1. XX
    Xin Xin

    Shandong University, China

    6 publications · 382 citations

    6

    h-index

  2. WP
    Weike Pan

    Shenzhen University, China

    6 publications · 129 citations

    6

    h-index

  3. JM
    Joemon M. Jose

    University of Glasgow, United Kingdom

    6 publications · 414 citations

    6

    h-index

  4. XH
    Xiangnan He

    University of Science and Technology of China, China

    6 publications · 8.2K citations

    6

    h-index

  5. TJ
    Thorsten Joachims

    Cornell University, United States

    5 publications · 623 citations

    5

    h-index

1–5 of 307

Institutions

133

  1. Shandong University

    Jinan, China

    7 h-index

    22 publications

    7.5K citations

  2. University of Glasgow

    Glasgow, United Kingdom

    7 h-index

    12 publications

    763 citations

  3. Shenzhen University

    Shenzhen, China

    6 h-index

    22 publications

    500 citations

  4. National University of Singapore

    Singapore, Singapore

    5 h-index

    13 publications

    25K citations

  5. University of Science and Technology of China

    Hefei, China

    4 h-index

    7 publications

    373 citations

  6. Tsinghua University

    Beijing, China

    4 h-index

    13 publications

    691 citations

  7. Microsoft (United States)

    Redmond, United States

    4 h-index

    5 publications

    175 citations

  8. Cornell University

    Ithaca, United States

    4 h-index

    7 publications

    1.7K citations

1–8 of 133

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 273 citations

    5

    h-index

  2. 3

    h-index

  3. Neurocomputing

    3 publications · 94 citations

    3

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 124 citations

    3

    h-index

  5. Knowledge-Based Systems

    3 publications · 222 citations

    3

    h-index

1–5