Data Query Resolution

Data Query Resolution is a methodological contribution in the field of data review that systematically identifies, prioritizes, and addresses anomalies, inconsistencies, or gaps in data through structured query formulation and validation to ensure data integrity and reliability.

27

Publications

2.9K

Citations

114

Authors

71

Institutions

Publications per year

2017–2026

10

Authors

114

  1. PS
    Peter Steenkiste

    Carnegie Mellon University, United States

    3 publications · 80 citations

    3

    h-index

  2. JG
    Jun Gao

    Carnegie Mellon University, United States

    3 publications · 80 citations

    3

    h-index

  3. GT
    George Tzanetakis

    University of Victoria, Canada

    2 publications · 27 citations

    2

    h-index

  4. PL
    Pierre Ledoux

    National Institutes of Health, United States

    1 publications · 1.5K citations

    1

    h-index

  5. YH
    Yanyan Han

    Wuhan University, China

    1 publications · 41 citations

    1

    h-index

1–5 of 114

Venues

  1. Fuzzy Sets and Systems

    2 publications · 54 citations

    2

    h-index

  2. Information Systems

    2 publications · 93 citations

    2

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 41 citations

    2

    h-index

  4. Nucleic Acids Research

    2 publications · 1.9K citations

    2

    h-index

  5. ACM Transactions on Graphics

    TOG · 1 publications · 13 citations

    1

    h-index

1–5