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Found 6 papers, 2 papers with code
Multifile Partitioning for Record Linkage and Duplicate Detection
Merging datafiles containing information on overlapping sets of entities is a challenging task in the absence of unique identifiers, and is further complicated when some entities are duplicated in the datafiles.
Nonparametric Pattern-Mixture Models for Inference with Missing Data
Pattern-mixture models provide a transparent approach for handling missing data, where the full-data distribution is factorized in a way that explicitly shows the parts that can be estimated from observed data alone, and the parts that require identifying restrictions.
Methodology Statistics Theory Statistics Theory
Least Ambiguous Set-Valued Classifiers with Bounded Error Levels
In most classification tasks there are observations that are ambiguous and therefore difficult to correctly label.
Bayesian Estimation of Bipartite Matchings for Record Linkage
The bipartite record linkage task consists of merging two disparate datafiles containing information on two overlapping sets of entities.
Detecting duplicates in a homicide registry using a Bayesian partitioning approach
Our Bayesian implementation allows us to incorporate prior information on the reliability of the fields in the data file, which is especially useful when no training data are available, and it also provides a proper account of the uncertainty in the duplicate detection decisions.
Applications Methodology
A Comparison of Blocking Methods for Record Linkage
Record linkage seeks to merge databases and to remove duplicates when unique identifiers are not available.
Databases Applications
