Fork of the Freely Extensible Biomedical Record Linkage program
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Updated
Nov 4, 2016 - Python
Entity resolution (also known as data matching, data linkage, record linkage, and many other terms) is the task of finding entities in a dataset that refer to the same entity across different data sources (e.g., data files, books, websites, and databases). Entity resolution is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g., database key, URI, National identification number), which may be due to differences in record shape, storage location, or curator style or preference.
Fork of the Freely Extensible Biomedical Record Linkage program
Mirror of https://bitbucket.org/resteorts/smered
My entry to a data analysis / record linkage coding challenge
A short guide to approximate geocoding
SAS-based standardizer for use in record linkage
Tools for improved blocking for historical record linkage
Data cleansing problem statement: Data in a record are often duplicated. How do we find the duplicate probability ? [Work In Progress]
Performs unique entity estimation corresponding to Chen, Shrivastava, Steorts (2018).
A Flask app to take IDs and resolve them to Wikidata URIs
A simple software that generates features and assess the accuracy of record linkage.
Implementation of DeepER system (record linkage with neural networks)
R Package and Shiny App to Analyze Insurance Lossruns
🆔 Command line tool for deduplicating CSV files
Link-Cov-P: An up-to-date and comprehensive bibliometric database on covid-19 research
The first micro-longitudinal bibliometric tracking of Covid-19 research's daily citation pattern
A workflow template for deduplication and record linkage using the Dedupe library
Phonetic Spelling Algorithms in Rust
Created by Halbert L. Dunn
Released 1946