Constraint-based Querying

Constraint-Based Querying is a visual querying method that restricts the search space through formally defined conditions or rules, enabling users to specify constraints on visual or semantic attributes to retrieve relevant data patterns or visualizations.

46

Publications

3.2K

Citations

85

Authors

41

Institutions

Publications per year

2017–2026

1

Authors

85

  1. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    4 publications · 895 citations

    4

    h-index

  2. LV
    Laks V. S. Lakshmanan

    University of British Columbia, Canada

    4 publications · 895 citations

    4

    h-index

  3. RT
    Raymond T. Ng

    University of British Columbia, Canada

    4 publications · 895 citations

    4

    h-index

  4. PR
    Péter Révész

    University of Nebraska–Lincoln, United States

    3 publications · 89 citations

    3

    h-index

  5. JS
    Jianwen Su

    University of California, Santa Barbara, United States

    3 publications · 126 citations

    3

    h-index

1–5 of 85

Venues

  1. ACM SIGMOD Record

    5 publications · 401 citations

    5

    h-index

  2. National Conference on Artificial Intelligence

    Conference · 2 publications · 68 citations

    2

    h-index

  3. Information Systems

    2 publications · 70 citations

    2

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 37 citations

    2

    h-index

  5. Journal of Computer and System Sciences

    2 publications · 258 citations

    2

    h-index

1–5