Fuzzy Community Detection

Fuzzy Community Detection is a community detection paradigm that, unlike crisp methods assigning each node to a single community, allows nodes to belong to multiple communities simultaneously with varying degrees of membership, thereby capturing overlapping community structures in networks.

43

Publications

2.7K

Citations

119

Authors

55

Institutions

Publications per year

2017–2026

20

Authors

119

  1. TC
    Timothy C. Havens

    Michigan Technological University, United States

    4 publications · 204 citations

    4

    h-index

  2. SB
    Susan Bastani

    Alzahra University, Iran

    3 publications · 75 citations

    3

    h-index

  3. MH
    Mohammad Hossein Fazel Zarandi

    Amirkabir University of Technology, Iran

    2 publications · 48 citations

    2

    h-index

  4. MN
    Mansoureh Naderipour

    Alzahra University, Iran

    2 publications · 48 citations

    2

    h-index

  5. JQ
    Junsheng Qiao

    Northwest Normal University, China

    2 publications · 66 citations

    2

    h-index

1–5 of 119

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 9 publications · 400 citations

    9

    h-index

  2. 5

    h-index

  3. Soft Computing

    2 publications · 61 citations

    2

    h-index

  4. Applied Soft Computing

    2 publications · 75 citations

    2

    h-index

  5. Journal of Statistical Mechanics Theory and Experiment

    JSTAT · 2 publications · 221 citations

    2

    h-index

1–5