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mbaak merged 1 commit into from
May 18, 2026
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Update README.md #49

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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -10,7 +10,7 @@
Entity Matching Model (EMM) solves the problem of matching company names between two possibly very
large datasets. EMM can match millions against millions of names with a distributed approach.
It uses the well-established candidate selection techniques in string matching,
namely: tfidf vectorization combined with cosine similarity (with significant optimization),
namely: tfidf vectorization combined with cosine similarity (with significant optimization, in part thanks to [sparse_dot_topn](https://github.com/ing-bank/sparse_dot_topn)),
both word-based and character-based, and sorted neighbourhood indexing.
These so-called indexers act complementary for selecting realistic name-pair candidates.
On top of the indexers, EMM has a classifier with optimized string-based, rank-based, and legal-entity
Expand Down Expand Up @@ -141,4 +141,4 @@ Please note that INGA-WB provides support only on a best-effort basis.

## License

Copyright ING WBAA 2023. Entity Matching Model is completely free, open-source and licensed under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).
Copyright ING WBAA 2026. Entity Matching Model is completely free, open-source and licensed under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).
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