Intra-sequence Mining

Intra-Sequence Mining is a subfield of sequence mining that focuses on discovering patterns, relationships, or structures within individual sequences, as opposed to across multiple sequences, by analyzing the internal ordering, timing, or composition of elements confined to a single sequence.

7

Publications

150

Citations

37

Authors

21

Institutions

Publications per year

2017–2026

2

Authors

37

  1. EC
    Enhong Chen

    University of Science and Technology of China, China

    1 publications · 23 citations

    1

    h-index

  2. LW
    Likang Wu

    University of Science and Technology of China, China

    1 publications · 23 citations

    1

    h-index

  3. HW
    Hao Wang

    University of Science and Technology of China, China

    1 publications · 23 citations

    1

    h-index

  4. WP
    Witold Pedrycz

    University of Alberta, Canada

    1 publications · 21 citations

    1

    h-index

  5. SK
    Seppe K. L. M. vanden Broucke

    KU Leuven, Belgium

    1 publications · 30 citations

    1

    h-index

1–5 of 37

Venues

  1. Applied Intelligence

    2 publications · 41 citations

    2

    h-index

  2. Expert Systems with Applications

    1 publications · 30 citations

    1

    h-index

  3. Geotechnical and Geological Engineering

    1 publications · 10 citations

    1

    h-index

  4. IEEE Communications Letters

    1 publications · 24 citations

    1

    h-index

  5. Information Processing Letters

    1 publications · 22 citations

    1

    h-index

1–5