Pagerank Centrality

PageRank Centrality is a network centrality measure that quantifies the importance of a node based on the likelihood of it being visited during a stochastic random walk, with transitions biased toward out-neighbors and occasionally redirected to random nodes through a teleportation mechanism.

137

Publications

5.8K

Citations

408

Authors

240

Institutions

Publications per year

2017–2026

75

Authors

408

  1. DL
    Dima L. Shepelyansky

    Université Toulouse III - Paul Sabatier, France

    4 publications · 104 citations

    4

    h-index

  2. GB
    Ginestra Bianconi

    Queen Mary University of London, United Kingdom

    4 publications · 365 citations

    4

    h-index

  3. TZ
    Ting Zhang

    Nanjing University of Science and Technology, China

    4 publications · 132 citations

    4

    h-index

  4. DB
    Dalal Bardou

    Abbès Laghrour University of Khenchela, Algeria

    4 publications · 142 citations

    4

    h-index

  5. GY
    Gaohang Yu

    Gannan Normal University, China

    3 publications · 100 citations

    3

    h-index

1–5 of 408

Venues

  1. Expert Systems with Applications

    5 publications · 304 citations

    5

    h-index

  2. IEEE Access

    5 publications · 110 citations

    5

    h-index

  3. PLoS ONE

    5 publications · 502 citations

    5

    h-index

  4. SSRN Electronic Journal

    Repository · 3 publications · 136 citations

    3

    h-index

  5. Scientometrics

    3 publications · 62 citations

    3

    h-index

1–5