This Julia package computes various distances between strings.

Distances

Edit Distances

• Hamming Distance
• Jaro Distance
• Levenshtein Distance
• Damerau-Levenshtein Distance
• RatcliffObershelp Distance (similar to the Python library difflib)

Q-Grams Distances

• QGram Distance
• Cosine Distance
• Jaccard Distance

A good reference for q-gram distances is the article written for the R package stringdist: The stringdist Package for Approximate String Matching Mark P.J. van der Loo

Syntax

evaluate

The function evaluate returns the litteral distance between two strings (a value of 0 being identical). While some distances are bounded by 1, other distances like Hamming, Levenshtein, Damerau-Levenshtein, Jaccard can be higher than 1.

using StringDistances
evaluate(Hamming(), "martha", "marhta")
#> 2
evaluate(QGram(2), "martha", "marhta")
#> 6

compare

The higher level function compare directly computes for any distance a similarity score between 0 and 1. A value of 0 being completely different and a value of 1 being completely similar.

using StringDistances
compare(Hamming(), "martha", "marhta")
#> 0.6666666666666667
compare(QGram(2), "martha", "marhta")
#> 0.4

Modifiers

The package defines a number of types to modify string metrics:

• Winkler boosts the similary score of strings with common prefixes

  compare(Jaro(), "martha", "marhta")
  #> 0.9444444444444445
  compare(Winkler(Jaro()), "martha", "marhta")
  #> 0.9611111111111111
  

  The Winkler adjustment was originally defined for the Jaro distance but this package defines it for any string distance.

  compare(QGram(2), "william", "williams")
  #> 0.9230769230769231
  compare(Winkler(QGram(2)), "william", "williams")
  #> 0.9538461538461539
  

• For strings composed of several words, the Python library fuzzywuzzy defines a few modifiers for the RatcliffObershelp distance. This package defines them for any string distance:

  • Partial adjusts for differences in string lengths. The function returns the maximal similarity score between the shorter string and all substrings of the longer string.

    compare(Partial(Hamming()), "New York Yankees", "Yankees")
    #> 1.0
    

  • TokenSort adjusts for differences in word orders by reording words alphabetically.

    compare(TokenSort(RatcliffObershelp()),"mariners vs angels", "angels vs mariners")
    #> 1.0
    

  • TokenSet adjusts for differences in word orders and word numbers.

    compare(TokenSet(RatcliffObershelp()),"mariners vs angels", "los angeles angels of anaheim at seattle mariners")