Personalized Group Recommendation

Personalized Group Recommendation is a group recommendation approach that integrates individual user preferences and behavioral patterns into the decision-making process to generate tailored recommendations for a group, distinguishing itself from general group recommendation methods by explicitly modeling personalization at both individual and collective levels.

56

Publications

2K

Citations

174

Authors

88

Institutions

Publications per year

2017–2026

35

Authors

174

  1. BD
    Belén Dí­az-Agudo

    Universidad Complutense de Madrid, Spain

    3 publications · 220 citations

    3

    h-index

  2. JA
    Juan A. Recio-Garcí­a

    Universidad Complutense de Madrid, Spain

    3 publications · 220 citations

    3

    h-index

  3. ZB
    Zahra Bahari Sojahrood

    K.N.Toosi University of Technology, Iran

    2 publications · 67 citations

    2

    h-index

  4. LB
    Ludovico Boratto

    University of Cagliari, Italy

    2 publications · 73 citations

    2

    h-index

  5. MT
    Mohammad Taleai

    K.N.Toosi University of Technology, Iran

    2 publications · 67 citations

    2

    h-index

1–5 of 174

Venues

  1. Expert Systems with Applications

    7 publications · 304 citations

    7

    h-index

  2. Information Sciences

    6 publications · 230 citations

    6

    h-index

  3. Information Processing & Management

    3 publications · 129 citations

    3

    h-index

  4. Neural Computing and Applications

    3 publications · 44 citations

    3

    h-index

  5. Neurocomputing

    3 publications · 71 citations

    3

    h-index

1–5