Content Recommendation Analysis

Content Recommendation Analysis is a scholarly analytical framework that systematically evaluates the effectiveness, relevance, and performance of algorithms or models designed to suggest digital content to users based on behavioral, contextual, or semantic criteria.

10

Publications

464

Citations

22

Authors

16

Institutions

Publications per year

2017–2026

7

Authors

22

  1. NG
    Niloy Ganguly

    Indian Institute of Technology Kharagpur, India

    2 publications · 82 citations

    2

    h-index

  2. JM
    Johnnatan Messias

    Universidade Federal de Minas Gerais, Brazil

    2 publications · 82 citations

    2

    h-index

  3. FB
    Fabrí­cio Benevenuto

    Universidade Federal de Minas Gerais, Brazil

    2 publications · 82 citations

    2

    h-index

  4. AC
    Abhijnan Chakraborty

    Indian Institute of Technology Kharagpur, India

    2 publications · 82 citations

    2

    h-index

  5. KP
    Krishna P. Gummadi

    Max Planck Institute for Software Systems, Germany

    2 publications · 82 citations

    2

    h-index

1–5 of 22

Venues

  1. Journal of Computer-Mediated Communication

    JCMC · 1 publications · 43 citations

    1

    h-index

  2. IEEE Signal Processing Magazine

    1 publications · 230 citations

    1

    h-index

  3. 1

    h-index

  4. Wireless Personal Communications

    1 publications · 16 citations

    1

    h-index

  5. Entertainment Computing

    1 publications · 12 citations

    1

    h-index

1–5