## vas-string-metrics

2021-12-09

Jaro-Winkler and Levenshtein string distance algorithms.

### Upstream URL

### Author

Vladimir Sedach <vsedach@gmail.com>

### License

Public Domain, LLGPLv3

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[1].
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.
[1] https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient#Applications