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  2. Rabin–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Rabin–Karp_algorithm

    However, it is a useful algorithm for multiple pattern search. To find any of a large number, say k, fixed length patterns in a text, a simple variant of the Rabin–Karp algorithm uses a Bloom filter or a set data structure to check whether the hash of a given string belongs to a set of hash values of patterns we are looking for:

  3. 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.

  4. Commentz-Walter algorithm - Wikipedia

    en.wikipedia.org/wiki/Commentz-Walter_algorithm

    Like the Aho–Corasick string matching algorithm, it can search for multiple patterns at once. It combines ideas from Aho–Corasick with the fast matching of the Boyer–Moore string-search algorithm. For a text of length n and maximum pattern length of m, its worst-case running time is O(mn), though the average case is often much better. [2]

  5. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot

  6. Regular expression - Wikipedia

    en.wikipedia.org/wiki/Regular_expression

    A regex pattern matches a target string. The pattern is composed of a sequence of atoms. An atom is a single point within the regex pattern which it tries to match to the target string. The simplest atom is a literal, but grouping parts of the pattern to match an atom will require using ( ) as metacharacters.

  7. Matching wildcards - Wikipedia

    en.wikipedia.org/wiki/Matching_wildcards

    In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]

  8. Boyer–Moore string-search algorithm - Wikipedia

    en.wikipedia.org/wiki/Boyer–Moore_string-search...

    P denotes the string to be searched for, called the pattern. Its length is m. S[i] denotes the character at index i of string S, counting from 1. S[i..j] denotes the substring of string S starting at index i and ending at j, inclusive. A prefix of S is a substring S[1..i] for some i in range [1, l], where l is the length of S.

  9. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    The patterns generally have the form of either sequences or tree structures. Uses of pattern matching include outputting the locations (if any) of a pattern within a token sequence, to output some component of the matched pattern, and to substitute the matching pattern with some other token sequence (i.e., search and replace).