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Common Optimizations for Levenshtein Edit Distance
I have been studying algorithms to compute the Levenshtein edit distance between two strings, which is defined as the minimum number of “edits” required to transform one string into another string. This is useful for a variety of things, from DNA sequence alignment to spell correction to address validation. I am studying it to resolve misspelled and OCR’ed scientific names of organisms to their real names, a famous problem in the field.
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