Natural Language Feedback Processing

Natural Language Feedback Processing is a computational framework within conversational recommendation systems that enables the interpretation and integration of user-generated natural language input to dynamically refine and personalize item recommendations.

62

Publications

2.6K

Citations

286

Authors

113

Institutions

Publications per year

2017–2026

52

Authors

286

  1. CC
    Changyou Chen

    University at Buffalo, State University of New York, United States

    2 publications · 46 citations

    2

    h-index

  2. TC
    Tat‐Seng Chua

    National University of Singapore, Singapore

    2 publications · 106 citations

    2

    h-index

  3. AS
    Andrew S. Gallan

    DePaul University, United States

    2 publications · 38 citations

    2

    h-index

  4. RZ
    Ruiyi Zhang

    Duke University, United States

    2 publications · 46 citations

    2

    h-index

  5. VR
    Verena Rieser

    Heriot-Watt University, United Kingdom

    2 publications · 50 citations

    2

    h-index

1–5 of 286

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 230 citations

    7

    h-index

  2. 2

    h-index

  3. Patient Experience Journal

    PXJ · 2 publications · 38 citations

    2

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 43 citations

    2

    h-index

  5. Frontiers in Public Health

    1 publications · 19 citations

    1

    h-index

1–5