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  2. 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; substitution: coat → cost

  3. Fuzzy matching (computer-assisted translation) - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_matching_(computer...

    The TM, in effect, "proposes" the match to the translator; it is then up to the translator to accept this proposal or to edit this proposal to more fully equate with the new source text that is undergoing translation. In this way, fuzzy matching can speed up the translation process and lead to increased productivity.

  4. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.

  5. Bitap algorithm - Wikipedia

    en.wikipedia.org/wiki/Bitap_algorithm

    The bitap algorithm (also known as the shift-or, shift-and or Baeza-Yates-Gonnet algorithm) is an approximate string matching algorithm. The algorithm tells whether a given text contains a substring which is "approximately equal" to a given pattern, where approximate equality is defined in terms of Levenshtein distance – if the substring and pattern are within a given distance k of each ...

  6. Function approximation - Wikipedia

    en.wikipedia.org/wiki/Function_approximation

    Several progressively more accurate approximations of the step function. An asymmetrical Gaussian function fit to a noisy curve using regression.. In general, a function approximation problem asks us to select a function among a well-defined class [citation needed] [clarification needed] that closely matches ("approximates") a target function [citation needed] in a task-specific way.

  7. Boyer–Moore string-search algorithm - Wikipedia

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

    This uses information gleaned during the pre-processing of the pattern in conjunction with suffix match lengths recorded at each match attempt. Storing suffix match lengths requires an additional table equal in size to the text being searched. The Raita algorithm improves the performance of Boyer–Moore–Horspool algorithm. The searching ...

  8. Nearest-neighbor interpolation - Wikipedia

    en.wikipedia.org/wiki/Nearest-neighbor_interpolation

    Interpolation is the problem of approximating the value of a function for a non-given point in some space when given the value of that function in points around (neighboring) that point. The nearest neighbor algorithm selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise ...

  9. sameAs - Wikipedia

    en.wikipedia.org/wiki/SameAs

    It provides a bit more flexibility by including variations and additional terms within the search query. This match type covers search terms that include your targeted keyword phrase, along with other words before or after it. When a shopper searches for a keyword phrase containing your targeted phrase and other terms, your ad may appear.