EmEditor’s Find and Replace feature fuzzy matching for finding close matches. String values in datasets may have spelling errors, so fuzzy matching helps with finding values that have slightly different spellings.
As an example, the strings
fuzzy matching and
fuzzx maching have an edit distance of 2 since it requires 2 changes for the strings to be equal. The first string is 14 characters, so if we did a fuzzy match for that string with a similarity level of 3 characters / 4 total characters, the second string is matched.