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- metrics of phrases differences, including soft Jaccard score (using Damerau-Levenshtein distance), and Word Mover's distance (WMD); (see :doc:`tutorial_metrics`)
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- character-level sequence-to-sequence (seq2seq) learning; (see :doc:`tutorial_charbaseseq2seq`)
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- spell correction; (see :doc:`tutorial_spell`)
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- API for word-embedding algorithm for one-time loading; (see :doc:`tutorial_wordembedAPI`) and
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- Sentence encodings and similarities based on BERT (see :doc:`tutorial_wordembed` and :doc:`tutorial_metrics`).
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Before release 0.7.2, part of the package was implemented using C, and it is interfaced to
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Python using SWIG_ (Simplified Wrapper and Interface Generator). Since 1.0.0, these implementations
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were replaced with Cython_.
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Author: Kwan Yuet Stephen Ho (LinkedIn_, ResearchGate_, Twitter_)
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