Frequent Subsequence Mining

Frequent Subsequence Mining is a data mining technique that identifies subsequences occurring with a frequency exceeding a predefined threshold within a sequence database, distinguishing it from other pattern mining methods by its focus on ordered but non-contiguous occurrences in sequential data.

156

Publications

11.1K

Citations

372

Authors

194

Institutions

Publications per year

2017–2026

26

Authors

372

  1. BL
    Bac Le

    Ho Chi Minh City University of Science, Vietnam

    5 publications · 125 citations

    5

    h-index

  2. ME
    Martin Ester

    Simon Fraser University, Canada

    5 publications · 864 citations

    5

    h-index

  3. JP
    Jian Pei

    Simon Fraser University, Canada

    4 publications · 2.1K citations

    4

    h-index

  4. PF
    Philippe Fournier‐Viger

    Harbin Institute of Technology, China

    4 publications · 99 citations

    4

    h-index

  5. JW
    Jianyong Wang

    Tsinghua University, China

    4 publications · 141 citations

    4

    h-index

1–5 of 372

Venues

  1. Information Processing Letters

    7 publications · 284 citations

    7

    h-index

  2. The VLDB Journal

    4 publications · 64 citations

    4

    h-index

  3. Theoretical Computer Science

    4 publications · 190 citations

    4

    h-index

  4. Knowledge and Information Systems

    4 publications · 208 citations

    4

    h-index

  5. Applied Intelligence

    4 publications · 75 citations

    4

    h-index

1–5