Audio-based Recommendation

Audio-Based Recommendation is a content-based recommendation approach that specifically utilizes audio signals as the primary input modality to extract and leverage acoustic features for generating personalized recommendations.

83

Publications

4.8K

Citations

238

Authors

82

Institutions

Publications per year

2017–2026

36

Authors

238

  1. MS
    Markus Schedl

    Johannes Kepler University of Linz, Austria

    8 publications · 190 citations

    8

    h-index

  2. YY
    Yi‐Hsuan Yang

    Academia Sinica, Taiwan

    4 publications · 106 citations

    4

    h-index

  3. YD
    Yashar Deldjoo

    Polytechnic University of Bari, Italy

    4 publications · 102 citations

    4

    h-index

  4. EZ
    Eva Zangerle

    Universität Innsbruck, Austria

    4 publications · 96 citations

    4

    h-index

  5. AF
    Arthur Flexer

    Austrian Research Institute for Artificial Intelligence, Austria

    4 publications · 73 citations

    4

    h-index

1–5 of 238

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 36 citations

    2

    h-index

  2. 2

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  3. Information Processing & Management

    2 publications · 252 citations

    2

    h-index

  4. Security and Communication Networks

    1 publications · 13 citations

    1

    h-index

  5. Applied Sciences

    1 publications · 85 citations

    1

    h-index

1–5