Data Matching Systems

Data Matching Systems is a systematic process within tax administration information systems that identifies and links corresponding records across disparate datasets by comparing key identifiers, distinguished by its application of algorithmic and statistical techniques to detect discrepancies, redundancies, or fraudulent declarations in taxpayer information.

29

Publications

2K

Citations

113

Authors

46

Institutions

Publications per year

2017–2026

9

Authors

113

  1. PK
    Pradap Konda

    University of Wisconsin–Madison, United States

    4 publications · 391 citations

    4

    h-index

  2. AD
    AnHai Doan

    University of Wisconsin–Madison, United States

    4 publications · 391 citations

    4

    h-index

  3. SD
    Sanjib Das

    Jadavpur University, India

    3 publications · 353 citations

    3

    h-index

  4. PS
    Paul Suganthan G. C.

    University of Wisconsin–Madison, United States

    3 publications · 369 citations

    3

    h-index

  5. HZ
    Haojun Zhang

    GlobalFoundries (United States), United States

    3 publications · 353 citations

    3

    h-index

1–5 of 113

Venues

  1. Communications of the ACM

    3 publications · 81 citations

    3

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 331 citations

    2

    h-index

  3. Information Technology and Libraries

    1 publications · 15 citations

    1

    h-index

  4. 1

    h-index

  5. Critical Sociology

    1 publications · 24 citations

    1

    h-index

1–5