Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends
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Updated
May 17, 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
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.
🔎 Finds fuzzy matches between datasets
🔎 Finds fuzzy matches between CSV files
This projects aims to provide lists containing only great movies to users based only a gew filters and search parameters.
Link Wikidata items to large catalogs
Resources for tackling record linkage / deduplication / data matching problems
A powerful and modular toolkit for record linkage and duplicate detection in Python
A list of free data matching and record linkage software.
Weka Comparator to match rules to test data with filtering abilites
ProxCluster is a framework for Incremental Entity Resolution that leverages concepts similar to K-Means for clustering duplicates. This work was developed as the final paper for my Bachelor degree in Computer Science
Fuzzy string matching in R. Inspired by Python's thefuzz (but without the Python).
A browser user interface for manual labeling of record pairs.
An extension for ASReview Lab to preprocess the dataset before importing in ASReview
A collection of awesome resources regarding Record Linkage.
Welcome to Snowman App – a Data Matching Benchmark Platform.
A maximum-strength name parser for record linkage.
PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
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.
Created by Halbert L. Dunn
Released 1946