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.
An open-source library that leverages Python’s data science ecosystem to build powerful end-to-end Entity Resolution workflows.
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 Winner-Take-All Hashing-Based Unsupervised Model for Entity Resolution Problems. [B. Sc. Thesis]
🧱 blocking methods for entity resolution
Experimental code for author name and affiliation linking/disabmiguation
BibLinkCreator Java library
backlink discovery, SEO, link-building
RoverCrawler is a single-file Python web crawler designed to explore websites and generate a tree-mapped representation of their structure.
Backlink Finder New 2026 is the premier utility for discovering high-authority link opportunities. Boost your SEO rankings and outpace competitors with this secure, high-speed discovery tool.
LIMES linking for data integration (D5.2)
Created by Halbert L. Dunn
Released 1946