Probabilistic Matching

Probabilistic Matching is a data integration method that belongs to the class of matching techniques and is distinguished by its use of statistical models to compute the likelihood of correspondences between records based on partial or uncertain attribute agreements.

215

Publications

15.1K

Citations

601

Authors

299

Institutions

Publications per year

2017–2026

32

Authors

601

  1. ER
    Edwin R. Hancock

    University of York, United Kingdom

    7 publications · 658 citations

    7

    h-index

  2. RC
    Richard C. Wilson

    University of York, United Kingdom

    4 publications · 140 citations

    4

    h-index

  3. AP
    Alex Pentland

    Massachusetts Institute of Technology, United States

    4 publications · 334 citations

    4

    h-index

  4. HG
    Harvey Goldstein

    University of Bristol, United Kingdom

    3 publications · 137 citations

    3

    h-index

  5. KH
    Katie Harron

    University College London, United Kingdom

    3 publications · 137 citations

    3

    h-index

1–5 of 601

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 11 publications · 1.3K citations

    11

    h-index

  2. Journal of the American Statistical Association

    5 publications · 2.8K citations

    5

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 47 citations

    3

    h-index

  4. PLoS ONE

    2 publications · 80 citations

    2

    h-index

  5. SPE Annual Technical Conference and Exhibition

    Conference · 2 publications · 89 citations

    2

    h-index

1–5