Visual Query Refinement

Visual Query Refinement is a visual interaction method that enables users to iteratively improve and narrow data queries through graphical representations and direct manipulation, distinguishing itself by integrating user feedback into the query process via real-time visual adjustments.

47

Publications

6.1K

Citations

167

Authors

68

Institutions

Publications per year

2017–2026

9

Authors

167

  1. TS
    Thomas Seidl

    RWTH Aachen University, Germany

    3 publications · 83 citations

    3

    h-index

  2. LZ
    Lei Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    2 publications · 146 citations

    2

    h-index

  3. SC
    Shi‐Kuo Chang

    University of Pittsburgh, United States

    2 publications · 39 citations

    2

    h-index

  4. ZW
    Zengfu Wang

    University of Science and Technology of China, China

    2 publications · 307 citations

    2

    h-index

  5. TC
    Tat‐Seng Chua

    National University of Singapore, Singapore

    2 publications · 153 citations

    2

    h-index

1–5 of 167

Venues

  1. 2

    h-index

  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 43 citations

    2

    h-index

  3. Choice Reviews Online

    CRO · 1 publications · 1.6K citations

    1

    h-index

  4. Egyptian Informatics Journal

    1 publications · 19 citations

    1

    h-index

  5. Expert Systems with Applications

    1 publications · 20 citations

    1

    h-index

1–5