The method was tailored to social sciences from a technique originally introduced to study molecular biology (protein or genetic) sequences (see sequence alignment).

- Optimal matchingSequence alignments are also used for non-biological sequences, such as calculating the distance cost between strings in a natural language or in financial data.

- Sequence alignmentLevenshtein distance may also be referred to as edit distance, although that term may also denote a larger family of distance metrics known collectively as edit distance.

- Levenshtein distanceLevenshtein distance operations are the removal, insertion, or substitution of a character in the string.

- Edit distanceIt is closely related to pairwise string alignments.

- Levenshtein distanceThe optimal match is denoted by the match that satisfies all the restrictions and the rules and that has the minimal cost, where the cost is computed as the sum of absolute differences, for each matched pair of indices, between their values.

- Dynamic time warpingThis sequence alignment method is often used in time series classification.

- Dynamic time warpingHirschberg's algorithm computes the optimal alignment of two strings, where optimality is defined as minimizing edit distance.

- Edit distanceThe methods used for biological sequence alignment have also found applications in other fields, most notably in natural language processing and in social sciences, where the Needleman-Wunsch algorithm is usually referred to as Optimal matching.

- Sequence alignment0 related topics