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To find multiple matches, the expected time is linear in the input lengths, plus the combined length of all the matches, which could be greater than linear. In contrast, the Aho–Corasick algorithm can find all matches of multiple patterns in worst-case time and space linear in the input length and the number of matches (instead of the total ...
A fuzzy Mediawiki search for "angry emoticon" has as a suggested result "andré emotions" In computer science, approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly).
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.
Fuzzy matching is a technique used in computer-assisted translation as a special case of record linkage.It works with matches that may be less than 100% perfect when finding correspondences between segments of a text and entries in a database of previous translations.
The complexity of the algorithm is linear in the length of the strings plus the length of the searched text plus the number of output matches. Note that because all matches are found, multiple matches will be returned for one string location if multiple substrings matched (e.g. dictionary = a, aa, aaa, aaaa and input string is aaaa).
In SQL, wildcard characters can be used in LIKE expressions; the percent sign % matches zero or more characters, and underscore _ a single character. Transact-SQL also supports square brackets ([and ]) to list sets and ranges of characters to match, a leading caret ^ negates the set and matches only a character not within the list.
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In mathematics, economics, and computer science, the stable marriage problem (also stable matching problem) is the problem of finding a stable matching between two equally sized sets of elements given an ordering of preferences for each element.