Record Linkage for Empirically Motivated Priors

An implementation of the model in Steorts (2015) , which performs Bayesian entity resolution for categorical and text data, for any distance function defined by the user. In addition, the precision and recall are in the package to allow one to compare to any other comparable method such as logistic regression, Bayesian additive regression trees (BART), or random forests. The experiments are reproducible and illustrated using a simple vignette.


Citation and Liscensing

This code is the main algorithm in Steorts (2015), Bayesian Analysis. If you use this code, please cite Steorts (2015), "Entity Resolution with Emprically Motivated Priors", Bayesian Analysis, (10),4:849-975.

This is a README for bLink. bLink Copyright 2015, 2016 Rebecca C. Steorts ([email protected])

bLink is free software, which is distributed under the Simple Public License 2.0 (SimPL-2.0 for short). See the license for more information regarding further use of code.

Code overview

In order to run the package in R, do the following. If you are running the code in Windows, you will need to install Rtools.

load(bLink)

For minimal testing purposes, see if you can load a function in bLink:

?mms()

This should call up a help file for one of the functions for the package.

Vignettes

  • There is an introduction to this package called introtobLink.html
  • This walks the user through an example using the data set RLData500 in R in the Record Linkage package.

News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("blink")

0.1.0 by Rebecca Steorts, 2 years ago


Browse source code at https://github.com/cran/blink


Authors: Rebecca Steorts [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports stats, utils

Depends on stringdist, RecordLinkage, plyr

Suggests knitr


See at CRAN