Frequent Tree Mining

Frequent Tree Mining is a computational method in the field of frequent pattern mining that identifies recurring tree-structured subgraphs within a dataset of tree-structured data, distinguished by its focus on discovering subtrees that appear with a frequency above a specified threshold.

126

Publications

6K

Citations

320

Authors

143

Institutions

Publications per year

2017–2026

12

Authors

320

  1. FH
    Fedja Hadzic

    Curtin University, Australia

    8 publications · 212 citations

    8

    h-index

  2. EC
    Elizabeth Chang

    Curtin University, Australia

    6 publications · 169 citations

    6

    h-index

  3. HT
    Henry Tan

    University of Technology Sydney, Australia

    6 publications · 173 citations

    6

    h-index

  4. TH
    Tzung‐Pei Hong

    National University of Kaohsiung, Taiwan

    6 publications · 380 citations

    6

    h-index

  5. RR
    Richard R. Muntz

    University of California, Los Angeles, United States

    6 publications · 715 citations

    6

    h-index

1–5 of 320

Venues

  1. Expert Systems with Applications

    4 publications · 409 citations

    4

    h-index

  2. Intelligent Data Analysis

    IDA · 3 publications · 57 citations

    3

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 488 citations

    3

    h-index

  4. 2

    h-index

  5. Knowledge and Information Systems

    2 publications · 114 citations

    2

    h-index

1–5