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Below are some examples of operations with buffer gaps. The gap is represented by the empty space between the square brackets. This representation is a bit misleading: in a typical implementation, the endpoints of the gap are tracked using pointers or array indices, and the contents of the gap are ignored; this allows, for example, deletions to be done by adjusting a pointer without changing ...
Presented here are two algorithms: the first, [8] simpler one, computes what is known as the optimal string alignment distance or restricted edit distance, [7] while the second one [9] computes the Damerau–Levenshtein distance with adjacent transpositions.
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.
For example, the strings "Sam" and "Samuel" can be considered to be close. [1] A string metric provides a number indicating an algorithm-specific indication of distance. The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). [2]
Any character may be used to separate the values, but the most common delimiters are the comma, tab, and colon. [2]: 113 [5] The vertical bar (also referred to as pipe) and space are also sometimes used. [2]: 113 Column headers are sometimes included as the first line, and each subsequent line is a row of data.
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Ukkonen's 1985 algorithm takes a string p, called the pattern, and a constant k; it then builds a deterministic finite state automaton that finds, in an arbitrary string s, a substring whose edit distance to p is at most k [13] (cf. the Aho–Corasick algorithm, which similarly constructs an automaton to search for any of a number of patterns ...
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