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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 requirement for a string metric (e.g. in contrast to string matching) is fulfillment of the triangle inequality. For example, the strings "Sam" and "Samuel" can be considered to be close. [1] A string metric provides a number indicating an algorithm-specific indication of distance.
Trigram search is a method of searching for text when the exact syntax or spelling of the target object is not precisely known [1] or when queries may be regular expressions. [2] It finds objects which match the maximum number of three consecutive character strings (i.e. trigrams) in the entered search terms, which are generally near matches. [3]
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.
With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched. String matching cannot be used for most binary data, such as images ...
If no matching characters are found then the strings are not similar and the algorithm terminates by returning Jaro similarity score 0. If non-zero matching characters are found, the next step is to find the number of transpositions. Transposition is the number of matching characters that are not in the right order divided by two.
A Dictionary-based Compressed Pattern Matching Algorithm (PDF), archived from the original (PDF) on March 13, 2003 "A unifying framework for compressed pattern matching". 1999: 89– 96. CiteSeerX 10.1.1.50.1745. {{cite journal}}: Cite journal requires |journal= "Speeding Up String Pattern Matching by Text Compression: The Dawn of a New Era" (PDF).
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]