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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. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    The function hamming_distance(), implemented in Python 3, computes the Hamming distance between two strings (or other iterable objects) of equal length by creating a sequence of Boolean values indicating mismatches and matches between corresponding positions in the two inputs, then summing the sequence with True and False values, interpreted as ...

  4. 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]

  5. 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.

  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. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched. String matching cannot be used for most binary data, such as images ...

  8. Dogs can match some words with objects, study suggests - AOL

    www.aol.com/dogs-match-words-objects-study...

    There was a two-second gap between owners saying the word of an object and showing it, a condition favoring the interpretation that dogs understood the words rather than simply associated them ...

  9. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    Edit distance finds applications in computational biology and natural language processing, e.g. the correction of spelling mistakes or OCR errors, and approximate string matching, where the objective is to find matches for short strings in many longer texts, in situations where a small number of differences is to be expected.