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  2. Jaro–Winkler distance - Wikipedia

    en.wikipedia.org/wiki/Jaro–Winkler_distance

    The higher the Jaro–Winkler distance for two strings is, the less similar the strings are. The score is normalized such that 0 means an exact match and 1 means there is no similarity. The original paper actually defined the metric in terms of similarity, so the distance is defined as the inversion of that value (distance = 1 − similarity).

  3. String metric - Wikipedia

    en.wikipedia.org/wiki/String_metric

    The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). [2] It operates between two input strings, returning a number equivalent to the number of substitutions and deletions needed in order to transform one input string into another.

  4. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]

  5. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...

  6. Dice-Sørensen coefficient - Wikipedia

    en.wikipedia.org/wiki/Dice-Sørensen_coefficient

    When taken as a string similarity measure, the coefficient may be calculated for two strings, x and y using bigrams as follows: [11] = + where n t is the number of character bigrams found in both strings, n x is the number of bigrams in string x and n y is the number of bigrams in string y. For example, to calculate the similarity between:

  7. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other.

  8. Minnesota Parents Who Locked Their Kids in Cages for ‘Their ...

    www.aol.com/lifestyle/minnesota-parents-locked...

    A Minnesota couple has reportedly been sentenced to four years after they locked their children in cages for "their safety." Benjamin and Christina Cotton from Red Wing, were sentenced by a ...

  9. Normalized compression distance - Wikipedia

    en.wikipedia.org/wiki/Normalized_compression...

    Normalized compression distance (NCD) is a way of measuring the similarity between two objects, be it two documents, two letters, two emails, two music scores, two languages, two programs, two pictures, two systems, two genomes, to name a few. Such a measurement should not be application dependent or arbitrary.