Rare Sequence Mining

Rare Sequence Mining is a sequence mining paradigm that identifies infrequent or low-support sequential patterns in a dataset, distinguishing itself from conventional sequence mining by focusing on rare occurrences that may signify exceptional or anomalous behaviors rather than prevalent trends.

10

Publications

537

Citations

49

Authors

14

Institutions

Publications per year

2017–2026

4

Authors

49

  1. PK
    Philippe Kourilsky

    Institut Pasteur, France

    1 publications · 72 citations

    1

    h-index

  2. CB
    Cassandra Buck

    Massachusetts General Hospital, United States

    1 publications · 174 citations

    1

    h-index

  3. ND
    Nicholas D. Watermeyer

    University of Cape Town, South Africa

    1 publications · 60 citations

    1

    h-index

  4. BF
    Brian F. Meyer

    King Faisal Specialist Hospital & Research Centre, Saudi Arabia

    1 publications · 174 citations

    1

    h-index

  5. RB
    Ravikumar Balasubramanian

    Massachusetts General Hospital, United States

    1 publications · 174 citations

    1

    h-index

1–5 of 49

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 1 publications · 62 citations

    1

    h-index

  2. European Journal of Immunology

    EJI · 1 publications · 72 citations

    1

    h-index

  3. IEEE Access

    1 publications · 43 citations

    1

    h-index

  4. Angewandte Chemie International Edition

    1 publications · 60 citations

    1

    h-index

  5. The Journal of Clinical Endocrinology & Metabolism

    JCEM · 1 publications · 174 citations

    1

    h-index

1–5