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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 ...
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
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]
This is the main difference between Diff-Text and most other text comparison algorithms. Diff-Text will always match up significant similarities even if contained within non-identical or moved lines. It never resorts to guessing or the first match that happens to be found, which may result in non-optimal matches elsewhere.
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 ...
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It specifies a limited subset of regular-expression idioms designed to be interoperable, i.e. produce the same effect, in a large number of regular-expression libraries. I-Regexp is also limited to matching, i.e. providing a true or false match between a regular expression and a given piece of text.
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