Levenshtein distance (edit distance) is the minimum number of character insertions, deletions, and substitutions required to transform one string into another. It was proposed by Russian mathematician Vladimir Levenshtein in 1965.

For example, the Levenshtein distance between "kitten" and "sitting" is 3 (k→s, e→i, insert g after n). This metric is widely applied in spell checking, fuzzy search, and DNA sequence comparison. String algorithms books cover calculation methods.

Calculation uses dynamic programming (DP) with time complexity O(mn) where m and n are the string lengths. Approximate algorithms may be used for large datasets.

For character counting, Levenshtein distance quantifies similarity between two texts at the character level, serving as a fundamental method for measuring character-level differences. NLP fundamentals books provide additional context.