Join GitHub today
GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together.Sign up
Jaro-Winkler and Levenshtein string distance algorithms for Common Lisp
Fetching latest commit…
Cannot retrieve the latest commit at this time.
|Type||Name||Latest commit message||Commit time|
|Failed to load latest commit information.|
vas-string-metrics provides the Jaro, Jaro-Winkler, Soerensen-Dice, Levenshtein, and normalized Levenshtein string distance/similarity metrics algorithms. The Jaro (function jaro-distance), Jaro-Winkler (function jaro-winkler-distance), Soerensen-Dice (function soerensen-dice-coefficient) and normalized Levenshtein (function normalized-levenshtein-distance) algorithms return a number in the range 0 to 1 indicating how similar two given strings are - where 0 indicates no similarity, and 1 indicatesa perfect match. The Jaro-Winkler metric is a heuristic suitable for shorter strings (such as place and people names), while the Levenshtein distance is computed as the minimum number of insertions, deletions, or substitutions needed to transform one string into the other (function levenshtein-distance). The Soerensen-Dice coefficient is a statistic suitable for heterogenous data sets and gives less weight to outliers. The code is distributed under the terms of the LLGPLv3 (see LICENSE for details), except for the unit tests, which are in the public domain.  https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient#Applications