Probabilistic Data Matching
Probabilistic Data Matching is a data integration method that identifies and links records from disparate sources by estimating the likelihood of correspondence based on weighted similarities across multiple fields, using statistical models to distinguish true matches from random coincidences.
46
Publications
1.9K
Citations
179
Authors
100
Institutions
Publications per year
2017–2026
9
Variants
Probabilistic Record Linkage
46
1–5 of 46
179
2
h-index
2
h-index
2
h-index
2
h-index
1
h-index
1–5 of 179
100
University of Oxford
Oxford, United Kingdom
2 h-index
3 publications
84 citations
Indiana University – Purdue University Indianapolis
Indianapolis, United States
2 h-index
6 publications
1.4K citations
Harvard University
Cambridge, United States
2 h-index
6 publications
254 citations

The University of Sydney
Sydney, Australia
2 h-index
5 publications
150 citations
University of Michigan
Ann Arbor, United States
2 h-index
2 publications
125 citations
University of California, Los Angeles
Los Angeles, United States
2 h-index
3 publications
70 citations
Indiana University School of Medicine
Indianapolis, United States
2 h-index
6 publications
1.4K citations
National Cancer Institute
Bethesda, United States
2 h-index
3 publications
117 citations
1–8 of 100
Repository · 3 publications · 56 citations
3
h-index
Repository · 2 publications · 54 citations
2
h-index
2 publications · 44 citations
2
h-index
2 publications · 58 citations
2
h-index
CSP · 1 publications · 22 citations
1
h-index
1–5