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For example, a text mentioning "daffodils" is probably closely related to a text mentioning "daffodil" (without the s). But in some cases, words with the same morphological stem have idiomatic meanings which are not closely related: a user searching for "marketing" will not be satisfied by most documents mentioning "markets" but not "marketing".
Regular expressions entered popular use from 1968 in two uses: pattern matching in a text editor [9] and lexical analysis in a compiler. [10] Among the first appearances of regular expressions in program form was when Ken Thompson built Kleene's notation into the editor QED as a means to match patterns in text files.
All methods have an unnamed parameter containing the text. The return value is an empty string if the parameter does not meet the conditions. When the condition is matched or some result is successfully found, strings of at least one character are returned.
In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]
In text processing, a proximity search looks for documents where two or more separately matching term occurrences are within a specified distance, where distance is the number of intermediate words or characters. In addition to proximity, some implementations may also impose a constraint on the word order, in that the order in the searched text ...
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Minutiae matching with those of other documents indicate shared text segments and suggest potential plagiarism if they exceed a chosen similarity threshold. [19] Computational resources and time are limiting factors to fingerprinting, which is why this method typically only compares a subset of minutiae to speed up the computation and allow for ...