Correlation Pattern Mining

Correlation Pattern Mining is a type of frequent pattern mining that identifies statistically significant associations among itemsets by measuring the strength and direction of their co-occurrence relationships beyond mere frequency thresholds.

70

Publications

3K

Citations

196

Authors

105

Institutions

Publications per year

2017–2026

17

Authors

196

  1. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    3 publications · 93 citations

    3

    h-index

  2. ZL
    Zhenmin Li

    University of Illinois Urbana-Champaign, United States

    2 publications · 231 citations

    2

    h-index

  3. WN
    Wilfred Ng

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 73 citations

    2

    h-index

  4. TH
    Tzung‐Pei Hong

    National University of Kaohsiung, Taiwan

    2 publications · 40 citations

    2

    h-index

  5. JC
    Jerry Chun‐Wei Lin

    Western Norway University of Applied Sciences, Norway

    2 publications · 86 citations

    2

    h-index

1–5 of 196

Venues

  1. Cluster Computing

    2 publications · 56 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 37 citations

    2

    h-index

  3. Information Sciences

    2 publications · 96 citations

    2

    h-index

  4. IEEE Access

    2 publications · 41 citations

    2

    h-index

  5. Electronics

    1 publications · 15 citations

    1

    h-index

1–5