Association Rule Learning

Association Rule Learning is an unsupervised learning method that identifies probabilistic relationships among variables in large datasets by discovering rules that describe how the occurrence of one set of items predicts the occurrence of another.

1.6K

Publications

137.8K

Citations

3.9K

Authors

1.4K

Institutions

Publications per year

2017–2026

399

Variants

Association Rule Analysis

Authors

3.9K

  1. RA
    Rakesh Agrawal

    IBM Research - Almaden, United States

    14 publications · 47.2K citations

    14

    h-index

  2. OR
    Osmar R. Zai͏̈ane

    University of Alberta, Canada

    13 publications · 1.2K citations

    13

    h-index

  3. SV
    Sebastián Ventura

    University of Córdoba, Spain

    14 publications · 627 citations

    13

    h-index

  4. TH
    Tzung‐Pei Hong

    National University of Kaohsiung, Taiwan

    13 publications · 468 citations

    12

    h-index

  5. FT
    Fadi Thabtah

    Manukau Institute of Technology, New Zealand

    13 publications · 784 citations

    12

    h-index

1–5 of 3.9K

Venues

  1. Expert Systems with Applications

    53 publications · 3.2K citations

    35

    h-index

  2. Information Sciences

    26 publications · 1.5K citations

    21

    h-index

  3. Knowledge-Based Systems

    24 publications · 1.3K citations

    19

    h-index

  4. Knowledge and Information Systems

    17 publications · 670 citations

    15

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 17 publications · 3.5K citations

    14

    h-index

1–5