Sequence Mining

Sequence Mining is a data mining technique that discovers frequent sequential patterns or ordered relationships among data items over time within a database, distinguishing it from other pattern mining methods by its focus on temporal or ordered occurrences.

1.6K

Publications

102.5K

Citations

3.4K

Authors

1.1K

Institutions

Publications per year

2017–2026

370

Authors

3.4K

  1. PF
    Philippe Fournier‐Viger

    Harbin Institute of Technology, China

    30 publications · 1.8K citations

    24

    h-index

  2. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    34 publications · 2.7K citations

    24

    h-index

  3. XW
    Xindong Wu

    Hefei University of Technology, China

    24 publications · 929 citations

    19

    h-index

  4. EK
    Eamonn Keogh

    University of California, Riverside, United States

    20 publications · 4.6K citations

    18

    h-index

  5. JP
    Jian Pei

    Simon Fraser University, Canada

    20 publications · 5K citations

    17

    h-index

1–5 of 3.4K

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 50 publications · 7.4K citations

    33

    h-index

  2. Information Sciences

    31 publications · 1.2K citations

    23

    h-index

  3. Knowledge and Information Systems

    28 publications · 1.5K citations

    22

    h-index

  4. Expert Systems with Applications

    31 publications · 1.8K citations

    22

    h-index

  5. Applied Intelligence

    25 publications · 849 citations

    18

    h-index

1–5