Metadata-based Recommendation

Metadata-Based Recommendation is a type of content-based recommendation approach that utilizes descriptive metadata associated with items to generate personalized suggestions by distinguishing item characteristics through structured attributes rather than raw content.

38

Publications

1.4K

Citations

125

Authors

57

Institutions

Publications per year

2017–2026

13

Authors

125

  1. MG
    Marcelo Garcia Manzato

    Universidade de São Paulo, Brazil

    3 publications · 56 citations

    3

    h-index

  2. RP
    Raluca Paiu

    L3S Research Center, Germany

    3 publications · 92 citations

    2

    h-index

  3. WN
    Wolfgang Nejdl

    L3S Research Center, Germany

    3 publications · 92 citations

    2

    h-index

  4. CS
    Claudiu S. Firan

    L3S Research Center, Germany

    3 publications · 92 citations

    2

    h-index

  5. KH
    Khalid Haruna

    Bayero University Kano, Nigeria

    2 publications · 37 citations

    2

    h-index

1–5 of 125

Venues

  1. Multimedia Tools and Applications

    3 publications · 113 citations

    3

    h-index

  2. International Symposium/Conference on Music Information Retrieval

    Conference · 1 publications · 18 citations

    1

    h-index

  3. IEEE Access

    1 publications · 17 citations

    1

    h-index

  4. Database

    1 publications · 25 citations

    1

    h-index

  5. Scientometrics

    1 publications · 20 citations

    1

    h-index

1–5