A Fuzzy Matching Approach for Clustering Strings
Project description
Fuzz Up [W.I.P.] 
fuzzup offers (1) a simple approach for clustering string entitities based on
Levenshtein Distance using
Fuzzy Matching
in conjunction with a simple rule-based clustering method.
fuzzup also provides (2) functions for computing the prominence of the resulting
entity clusters resulting from (1).
fuzzup has been designed to fit the output from NER predictions from the Hugging Face transformers NER pipeline specifically.
Installation guide
fuzzup can be installed from the Python Package Index (PyPI) by:
pip install fuzzup
If you want the development version then install directly from Github.
Workflow
... COMING SOON!
Background
fuzzup is developed as a part of Ekstra Bladet’s activities on Platform Intelligence in News (PIN). PIN is an industrial research project that is carried out in collaboration between the Technical University of Denmark, University of Copenhagen and Copenhagen Business School with funding from Innovation Fund Denmark. The project runs from 2020-2023 and develops recommender systems and natural language processing systems geared for news publishing, some of which are open sourced like fuzzup.
Read more
The detailed documentation and motivation for fuzzup including code references and
extended workflow examples can be accessed here.
Contact
We hope, that you will find fuzzup useful.
Please direct any questions and feedbacks to us!
If you want to contribute (which we encourage you to), open a PR.
If you encounter a bug or want to suggest an enhancement, please open an issue.
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