Visual Data Mining

Visual Data Mining is an academic concept that refers to a human-centred process of discovering implicit, previously unknown, and valuable patterns in data through interactive visual interfaces, distinguished from automated data mining by its emphasis on integrating human judgment and perceptual cognition into the analytical workflow.

1.4K

Publications

78K

Citations

4K

Authors

1.3K

Institutions

Publications per year

2017–2026

417

Authors

4K

  1. DA
    Daniel A. Keim

    University of Konstanz, Germany

    19 publications · 3.7K citations

    17

    h-index

  2. JY
    Junsong Yuan

    Nanyang Technological University, Singapore

    12 publications · 360 citations

    12

    h-index

  3. SC
    Shu‐Ching Chen

    Florida International University, United States

    14 publications · 541 citations

    12

    h-index

  4. MS
    Mei‐Ling Shyu

    University of Miami, United States

    15 publications · 579 citations

    12

    h-index

  5. HQ
    Huamin Qu

    Hong Kong University of Science and Technology, Hong Kong SAR China

    11 publications · 918 citations

    11

    h-index

1–5 of 4K

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 43 publications · 5.5K citations

    34

    h-index

  2. Expert Systems with Applications

    18 publications · 1K citations

    15

    h-index

  3. Neurocomputing

    15 publications · 1K citations

    13

    h-index

  4. Multimedia Tools and Applications

    13 publications · 440 citations

    13

    h-index

  5. Procedia Computer Science

    10 publications · 402 citations

    10

    h-index

1–5