Glob for C++17
Entity resolution for Elasticsearch.
Compares two names and gives a score or similarity percentage.
Deep fuzzy matching people and company names for multilingual entity resolution using representation learning
Packages for downloading the World Checklist of Vascular Plants (WCVP) and resolving plant names to it
A robust name matching library for Node.js that combines multiple string similarity algorithms for optimal name matching performance.
Find the best fuzzy match for a natural language string in a set of hundreds of thousands of strings in a split second.
Extract the components of a person or couples full name, from free form text
A simple python class for fuzzy name matching
Sentence similarity searching with SentenceTransformer
Generates a match score of two person names from 0-100, where 100 is the highest, on how closely two individual full names match. The scoring is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge
Repository associated to the publication: Llavero-Pasquina, M. (2025) Driving ecologically unequal exchange: A global analysis of multinational corporations’ role in environmental conflicts
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