Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends
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Updated
Sep 11, 2024 - 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.
Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends
A powerful and modular toolkit for record linkage and duplicate detection in Python
A list of free data matching and record linkage software.
Record linking package that fuzzy matches two Python pandas dataframes using sqlite3 fts4
🔎 Finds fuzzy matches between CSV files
PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
Resources for tackling record linkage / deduplication / data matching problems
Link Wikidata items to large catalogs
An open-source library that leverages Python’s data science ecosystem to build powerful end-to-end Entity Resolution workflows.
Curated list of awesome software and resources for Senzing, The First Real-Time AI for Entity Resolution.
A browser user interface for manual labeling of record pairs.
Welcome to Snowman App – a Data Matching Benchmark Platform.
Fuzzy string matching in R. Inspired by Python's thefuzz (but without the Python).
A maximum-strength name parser for record linkage.
Compound AI toolchain for fast and accurate entity matching, powered by LLMs.
🔎 Finds fuzzy matches between datasets
WInte.r is a Java framework for end-to-end data integration. The WInte.r framework implements well-known methods for data pre-processing, schema matching, identity resolution, data fusion, and result evaluation.
A collection of awesome resources regarding Record Linkage.
Emulates the methods the US Census Bureau uses to link people across multiple data sources, using open-source software (Splink) and simulated data (from pseudopeople).
Created by Halbert L. Dunn
Released 1946