Cross-database Matching

Cross-Database Matching is a re-identification technique that involves linking anonymous records across distinct databases by identifying common attributes or patterns, thereby distinguishing itself from within-database methods through its reliance on external data sources to infer individual identities.

67

Publications

4.3K

Citations

241

Authors

128

Institutions

Publications per year

2017–2026

31

Variants

Cross-database Record Linkage

Authors

241

  1. TM
    Timothy M. Smeeding

    University of Wisconsin–Madison, United States

    3 publications · 93 citations

    3

    h-index

  2. PW
    Philipp Werner

    Otto-von-Guericke-Universität Magdeburg, Germany

    3 publications · 82 citations

    3

    h-index

  3. AB
    Andrea Brandolini

    Bank of Italy, Italy

    3 publications · 93 citations

    3

    h-index

  4. MP
    Maja Pantić

    Imperial College London, United Kingdom

    3 publications · 466 citations

    3

    h-index

  5. AA
    Ayoub Al-Hamadi

    Otto-von-Guericke-Universität Magdeburg, Germany

    3 publications · 82 citations

    3

    h-index

1–5 of 241

Venues

  1. SSRN Electronic Journal

    Repository · 3 publications · 93 citations

    3

    h-index

  2. 2009 IEEE Conference on Computer Vision and Pattern Recognition

    Conference · 2 publications · 98 citations

    2

    h-index

  3. Sensors

    2 publications · 38 citations

    2

    h-index

  4. 2

    h-index

  5. 1

    h-index

1–5