Interactive Pattern Discovery

Interactive Pattern Discovery is a computational method that enables users to iteratively explore, refine, and extract meaningful patterns from complex datasets through real-time human-in-the-loop interactions.

26

Publications

1.2K

Citations

92

Authors

42

Institutions

Publications per year

2017–2026

2

Authors

92

  1. SL
    Suh-Yin Lee

    National Yang Ming Chiao Tung University, Taiwan

    2 publications · 35 citations

    2

    h-index

  2. ML
    Ming-Yen Lin

    Feng Chia University, Taiwan

    2 publications · 35 citations

    2

    h-index

  3. SJ
    Steven J.M. Jones

    Canada's Michael Smith Genome Sciences Centre, Canada

    2 publications · 76 citations

    2

    h-index

  4. AH
    Andreas Holzinger

    Medical University of Graz, Austria

    2 publications · 289 citations

    2

    h-index

  5. AC
    Andrea Colaço

    Massachusetts Institute of Technology, United States

    1 publications · 78 citations

    1

    h-index

1–5 of 92

Venues

  1. Information Visualization

    2 publications · 134 citations

    2

    h-index

  2. 2

    h-index

  3. 1

    h-index

  4. Genome biology

    1 publications · 41 citations

    1

    h-index

  5. Bioinformatics

    1 publications · 24 citations

    1

    h-index

1–5