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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]
In mathematics and computer science, a string metric (also known as a string similarity metric or string distance function) is a metric that measures distance ("inverse similarity") between two text strings for approximate string matching or comparison and in fuzzy string searching.
Symbolic entities can be introduced to represent many different classes of relevant features of a string. For instance, StringExpression[LetterCharacter, DigitCharacter] will match a string that consists of a letter first, and then a number. In Haskell, guards could be used to achieve the same matches:
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).
Traditionally, approximate string matching algorithms are classified into two categories: online and offline. With online algorithms the pattern can be processed before searching but the text cannot. With online algorithms the pattern can be processed before searching but the text cannot.
where is the common aligned length of the two texts A and B, and the bracketed term is defined as 1 if the -th letter of text A matches the -th letter of text B, otherwise 0. A related concept, the "bulge" of a distribution, measures the discrepancy between the observed I.C. and the null value of 1.0.
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.
This parser function can be used to detect whether a template parameter is defined, even if it has been set to a false value. For example, to check whether the first positional parameter has been passed to a template (note that the strings "+" and "-" can be any two different non-whitespace strings):