Exploring linking records from disparate data sources
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Updated
Jun 22, 2022 - C#
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.
Exploring linking records from disparate data sources
library for dataset comparison
The StringMetrics project implements 7 string metric algorithms: Hamming, Dice, Jaro, Jaro-Winkler, Soundex, Levenshtein, and Damerau-Levenshtein. Metrics compare strings using IMetric interface providing an approximate similarity score from 0 (no match) to 1 (exact match) useful in data cleansing, record linkage, NLP, fraud detection, etc.
Created by Halbert L. Dunn
Released 1946