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  2. Aho–Corasick algorithm - Wikipedia

    en.wikipedia.org/wiki/Aho–Corasick_algorithm

    Aho–Corasick algorithm. In computer science, the Aho–Corasick algorithm is a string-searching algorithm invented by Alfred V. Aho and Margaret J. Corasick in 1975. [1] It is a kind of dictionary-matching algorithm that locates elements of a finite set of strings (the "dictionary") within an input text. It matches all strings simultaneously.

  3. Two-way string-matching algorithm - Wikipedia

    en.wikipedia.org/wiki/Two-way_string-matching...

    In computer science, the two-way string-matching algorithm is a string-searching algorithm, discovered by Maxime Crochemore and Dominique Perrin in 1991. [1] It takes a pattern of size m, called a “needle”, preprocesses it in linear time O(m), producing information that can then be used to search for the needle in any “haystack” string, taking only linear time O(n) with n being the ...

  4. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    In computer science, approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly). The problem of approximate string matching is typically divided into two sub-problems: finding approximate substring matches inside a given ...

  5. Knuth–Morris–Pratt algorithm - Wikipedia

    en.wikipedia.org/wiki/Knuth–Morris–Pratt...

    In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.

  6. Needleman–Wunsch algorithm - Wikipedia

    en.wikipedia.org/wiki/Needleman–Wunsch_algorithm

    The algorithm essentially divides a large problem (e.g. the full sequence) into a series of smaller problems, and it uses the solutions to the smaller problems to find an optimal solution to the larger problem. [2] It is also sometimes referred to as the optimal matching algorithm and the global alignment technique. The Needleman–Wunsch ...

  7. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    This algorithm, an example of bottom-up dynamic programming, is discussed, with variants, in the 1974 article The String-to-string correction problem by Robert A. Wagner and Michael J. Fischer. [ 4 ] This is a straightforward pseudocode implementation for a function LevenshteinDistance that takes two strings, s of length m , and t of length n ...

  8. Parsing expression grammar - Wikipedia

    en.wikipedia.org/wiki/Parsing_expression_grammar

    A parsing expression is a kind of pattern that each string may either match or not match.In case of a match, there is a unique prefix of the string (which may be the whole string, the empty string, or something in between) which has been consumed by the parsing expression; this prefix is what one would usually think of as having matched the expression.

  9. Damerau–Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Damerau–Levenshtein_distance

    Damerau–Levenshtein distance. In information theory and computer science, the Damerau–Levenshtein distance (named after Frederick J. Damerau and Vladimir I. Levenshtein [1][2][3]) is a string metric for measuring the edit distance between two sequences. Informally, the Damerau–Levenshtein distance between two words is the minimum number ...

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