Frequent Pattern Evaluation

Frequent Pattern Evaluation is a methodological framework within pattern evaluation that specifically assesses the significance, validity, and utility of recurring structures or itemsets in data by measuring their frequency, support, and relevance relative to a given threshold or domain context.

88

Publications

4.8K

Citations

266

Authors

116

Institutions

Publications per year

2017–2026

18

Authors

266

  1. CZ
    Chengqi Zhang

    University of Technology Sydney, Australia

    3 publications · 70 citations

    3

    h-index

  2. LL
    Lotfi Lakhal

    Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes, France

    2 publications · 135 citations

    2

    h-index

  3. FS
    Fiona S. L. Brinkman

    Simon Fraser University, Canada

    2 publications · 100 citations

    2

    h-index

  4. PT
    Pang‐Ning Tan

    Michigan State University, United States

    2 publications · 216 citations

    2

    h-index

  5. RS
    Rong She

    Simon Fraser University, Canada

    2 publications · 100 citations

    2

    h-index

1–5 of 266

Venues

  1. Knowledge-Based Systems

    3 publications · 207 citations

    3

    h-index

  2. Expert Systems with Applications

    3 publications · 209 citations

    3

    h-index

  3. Knowledge and Information Systems

    2 publications · 73 citations

    2

    h-index

  4. Bioinformatics

    2 publications · 116 citations

    2

    h-index

  5. Data Archiving and Networked Services (DANS)

    Repository · 2 publications · 37 citations

    2

    h-index

1–5