Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects simply to a non-technical, business audience. Over…
Fuzzy matching is a method that provides an improved ability to process word-based matching queries to find matching phrases or sentences from a database. When an exact match is not found for a sentence or phrase, fuzzy matching can be applied. Fuzzy matching attempts to find a match which, although not a 100 percent match, is above the threshold matching percentage set by the application.
Fuzzy matching is mainly used in computer-assisted translation and other related applications.
Fuzzy matching searches a translation memory database for a query’s phrases or words, finding derivatives by suggesting words with approximate matching in meanings as well as spellings.
The fuzzy matching technique applies a matching percentage. The database returns possible matches for the queried word between a certain percentage (the threshold percentage) and 100 percent.
So far, fuzzy matching is not capable of replacing humans in language translation processing, but with more research and artificial intelligence technique application, it may be capable of replacing humans in the future with nearly 100 percent accuracy.
Fuzzy matching-based translation software is available and is used to generate a basic translated form, which can be manually processed to reach a final, readable form.
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Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.
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