April 2009 : Cogen uses Levenshtein algorithm to calculate fuzzy matching
Fuzzy matching is a popular method for leveraging content from a translation memory, where matches are less than 100% perfect, ie. are not "full matches".
Cogen has now re-written its fuzzy matching algorithm to incorporate the edit distance measurement as defined by Russian scientist Vladimir Levenshtein. The Levenshtein distance is a metric used for measuring the difference between two sequences (ie. the "edit distance"). It is often used in applications that need to determine how similar, or different, two character strings are - such as spell checkers.
In the application of Translation Memory, the Levenshtein algorithm offers some major advantages:
It is rigorously precise in calculating the matching percentage. In our algorithm, the "fuzziness" treshold is set at 60%: as soon as 60% of the content matches, two segments are considered to have a fuzzy match, which reduces the translation fee by 50%. Consequently, the translation fees for fuzzy matches are more economical than the translation industry's commonly used standard.
The algorithm is perfectly suited to logographic writing systems such as Chinese and Japanese.
It increases translation memory reuse, reducing the translation turnaround time, and improving the translation quality.
To receive a copy of Cogen's white paper on the Levenshtein algorithm, please contact:
Jean Mandron, Business Development Manager
(+33 1 46 91 89 14,
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Hélène Keufgens, CEO
(+32 6789 2514,
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