Sequential Data Preprocessing

Sequential Data Preprocessing is a methodological procedure that transforms raw sequential data into a structured, analyzable form by applying operations such as noise filtering, gap filling, alignment, and representation conversion to facilitate subsequent sequence mining tasks.

115

Publications

6.5K

Citations

421

Authors

205

Institutions

Publications per year

2017–2026

55

Authors

421

  1. FM
    Federico Marini

    Sapienza University of Rome, Italy

    3 publications · 172 citations

    3

    h-index

  2. JR
    Jean‐Michel Roger

    Technologies & méthodes pour les agricultures de demain, France

    3 publications · 172 citations

    3

    h-index

  3. AB
    Alessandra Biancolillo

    University of L'Aquila, Italy

    3 publications · 172 citations

    3

    h-index

  4. PM
    Puneet Mishra

    Wageningen University & Research, Netherlands

    3 publications · 102 citations

    3

    h-index

  5. PS
    Penelope Sanderson

    The University of Queensland, Australia

    2 publications · 362 citations

    2

    h-index

1–5 of 421

Venues

  1. Psychological Bulletin

    5 publications · 508 citations

    5

    h-index

  2. IEEE Access

    3 publications · 201 citations

    3

    h-index

  3. 3

    h-index

  4. Data & Knowledge Engineering

    DKE · 2 publications · 132 citations

    2

    h-index

  5. 2

    h-index

1–5