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  2. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.

  3. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    When matching database relates to a large scale of data, the O(mn) time with the dynamic programming algorithm cannot work within a limited time. So, the idea is to reduce the number of candidate pairs, instead of computing the similarity of all pairs of strings.

  4. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.

  5. 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 ...

  6. 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 ...

  7. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The longest common substrings of a set of strings can be found by building a generalized suffix tree for the strings, and then finding the deepest internal nodes which have leaf nodes from all the strings in the subtree below it. The figure on the right is the suffix tree for the strings "ABAB", "BABA" and "ABBA", padded with unique string ...

  8. Rabin–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Rabin–Karp_algorithm

    To find a single match of a single pattern, the expected time of the algorithm is linear in the combined length of the pattern and text, although its worst-case time complexity is the product of the two lengths. To find multiple matches, the expected time is linear in the input lengths, plus the combined length of all the matches, which could ...

  9. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    By far the most common form of pattern matching involves strings of characters. In many programming languages, a particular syntax of strings is used to represent regular expressions, which are patterns describing string characters. However, it is possible to perform some string pattern matching within the same framework that has been discussed ...