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An example of the Scunthorpe problem in Wikipedia because of a regular expression identifying "cunt" in the username. The Scunthorpe problem is the unintentional blocking of online content by a spam filter or search engine because their text contains a string (or substring) of letters that appear to have an obscene or otherwise unacceptable meaning.
contains(string,substring) returns boolean Description Returns whether string contains substring as a substring. This is equivalent to using Find and then detecting that it does not result in the failure condition listed in the third column of the Find section. However, some languages have a simpler way of expressing this test. Related
If is a substring of , it is also a subsequence, which is a more general concept. The occurrences of a given pattern in a given string can be found with a string searching algorithm. Finding the longest string which is equal to a substring of two or more strings is known as the longest common substring problem.
In the array containing the E(x, y) values, we then choose the minimal value in the last row, let it be E(x 2, y 2), and follow the path of computation backwards, back to the row number 0. If the field we arrived at was E(0, y 1), then T[y 1 + 1] ... T[y 2] is a substring of T with the minimal edit distance to the pattern P.
For readability, the CYK table for P is represented here as a 2-dimensional matrix M containing a set of non-terminal symbols, such that R k is in [,] if, and only if, [,,] . In the above example, since a start symbol S is in M [ 7 , 1 ] {\displaystyle M[7,1]} , the sentence can be generated by the grammar.
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
In theory, a reverse dictionary might go further than this, allowing you to find a word by its definition only (for example, to find the word "doctor" knowing only that he is a "person who cures disease"). Such dictionaries have become more practical with the advent of computerized information-storage and retrieval systems (i.e. computer ...
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.