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The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot
When an exact match cannot be found in the TM database for the text being translated, there is an option to search for a match that is less than exact; the translator sets the threshold of the fuzzy match to a percentage value less than 100%, and the database will then return any matches in its memory corresponding to that percentage.
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.
Search for an exact string using a simple regexp; pretest a small search domain. Hack out a highly refined set of page characteristics with concern only for an exact count of pages; refine in a sandbox and on the search results page. The concept of a search domain plays an important part in all this. By default it is just article space, but in ...
The average number of characters in any given word on a page may be estimated at 5 (Wikipedia:Size comparisons) Given this scenario, an uncompressed index (assuming a non-conflated, simple, index) for 2 billion web pages would need to store 500 billion word entries. At 1 byte per character, or 5 bytes per word, this would require 2500 gigabytes ...
The concept of sameAs exists in a number of different schemas and systems: JSON-LD [1] OWL - owl:sameAs [2] schema.org [3] SKOS - skos:exactMatch [4] Wikidata - Property:P2888 "exact match", with the alias "sameas" [5] The owl:sameAs predicate has been described as "an essential ingredient of the Semantic Web architecture". [2]
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]
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 ...