Friendship-based Recommendation

Friendship-Based Recommendation is a social recommendation approach that leverages explicit friendship ties in social networks to infer user preferences, distinguishing itself from other social recommendation methods by prioritizing direct, dyadic social relationships as the primary source of influence in personalized ranking or prediction.

173

Publications

12.3K

Citations

597

Authors

249

Institutions

Publications per year

2017–2026

64

Authors

597

  1. AC
    Alvin Chin

    Nokia (China), China

    4 publications · 60 citations

    4

    h-index

  2. PS
    Panagiotis Symeonidis

    Aristotle University of Thessaloniki, Greece

    3 publications · 155 citations

    3

    h-index

  3. WL
    Wang-Chien Lee

    Pennsylvania State University, United States

    3 publications · 813 citations

    3

    h-index

  4. YM
    Yannis Manolopoulos

    Aristotle University of Thessaloniki, Greece

    3 publications · 155 citations

    3

    h-index

  5. YT
    Yong Tang

    South China University of Technology, China

    2 publications · 31 citations

    2

    h-index

1–5 of 597

Venues

  1. IEEE Access

    6 publications · 126 citations

    6

    h-index

  2. Social Network Analysis and Mining

    4 publications · 202 citations

    4

    h-index

  3. Expert Systems with Applications

    4 publications · 214 citations

    4

    h-index

  4. Decision Support Systems

    3 publications · 99 citations

    3

    h-index

  5. Information Sciences

    3 publications · 253 citations

    3

    h-index

1–5