Emerging Pattern Mining

Emerging Pattern Mining is a type of frequent pattern mining that identifies itemsets whose support significantly increases from one transaction dataset to another, typically across different time periods or classes, thereby capturing evolving patterns indicative of emerging trends or shifts in data behavior.

47

Publications

2.8K

Citations

109

Authors

59

Institutions

Publications per year

2017–2026

10

Authors

109

  1. KR
    Kotagiri Ramamohanarao

    The University of Melbourne, Australia

    7 publications · 348 citations

    7

    h-index

  2. HL
    Harco Leslie Hendric Spits Warnars

    Binus University, Indonesia

    5 publications · 88 citations

    5

    h-index

  3. KY
    Kui Yu

    Hefei University of Technology, China

    3 publications · 69 citations

    3

    h-index

  4. XW
    Xindong Wu

    Hefei University of Technology, China

    3 publications · 69 citations

    3

    h-index

  5. MJ
    María José del Jesús

    Universidad de Jaén, Spain

    3 publications · 79 citations

    3

    h-index

1–5 of 109

Venues

  1. Journal of Chemical Information and Modeling

    JCIM · 2 publications · 60 citations

    2

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 115 citations

    2

    h-index

  3. 2

    h-index

  4. Education and Information Technologies

    1 publications · 25 citations

    1

    h-index

  5. 1

    h-index

1–5