text-metrics-0.3.3: Calculate various string metrics efficiently

Copyright | © 2016–present Mark Karpov
License | BSD 3 clause
Maintainer | Mark Karpov <markkarpov92@gmail.com>
Stability | experimental
Portability | portable
Safe Haskell | None
Language | GHC2021

Data.Text.Metrics

Contents

- Levenshtein variants
- Treating inputs like sets
- Other

Description

The module provides efficient implementations of various strings metric algorithms. It works with strict `Text` values.

Note: before version 0.3.0 the package used C implementations of the algorithms under the hood. Beginning from version 0.3.0, the implementations are written in Haskell while staying almost as fast, see:

https://markkarpov.com/post/migrating-text-metrics.html

Synopsis

- levenshtein :: Text -> Text -> Int
- levenshteinNorm :: Text -> Text -> Ratio Int
- damerauLevenshtein :: Text -> Text -> Int
- damerauLevenshteinNorm :: Text -> Text -> Ratio Int
- overlap :: Text -> Text -> Ratio Int
- jaccard :: Text -> Text -> Ratio Int
- hamming :: Text -> Text -> Maybe Int
- jaro :: Text -> Text -> Ratio Int
- jaroWinkler :: Text -> Text -> Ratio Int

# Levenshtein variants

levenshtein :: Text -> Text -> Int Source #

Return the Levenshtein distance between two `Text` values. The Levenshtein distance between two strings is the minimal number of operations necessary to transform one string into another. For the Levenshtein distance allowed operations are: deletion, insertion, and substitution.

See also: https://en.wikipedia.org/wiki/Levenshtein_distance.

Heads up, before version 0.3.0 this function returned `Natural`.

levenshteinNorm :: Text -> Text -> Ratio Int Source #

Return the normalized Levenshtein distance between two `Text` values. Result is a non-negative rational number (represented as ``Ratio` `Natural``), where 0 signifies no similarity between the strings, while 1 means exact match.

See also: https://en.wikipedia.org/wiki/Levenshtein_distance.

Heads up, before version 0.3.0 this function returned ``Ratio` `Natural``.

damerauLevenshtein :: Text -> Text -> Int Source #

Return the Damerau-Levenshtein distance between two `Text` values. The function works like `levenshtein`, but the collection of allowed operations also includes transposition of two adjacent characters.

See also: https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance.

Heads up, before version 0.3.0 this function returned `Natural`.

damerauLevenshteinNorm :: Text -> Text -> Ratio Int Source #

Return the normalized Damerau-Levenshtein distance between two `Text` values. 0 signifies no similarity between the strings, while 1 means exact match.

See also: https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance.

Heads up, before version 0.3.0 this function returned ``Ratio` `Natural``.

# Treating inputs like sets

overlap :: Text -> Text -> Ratio Int Source #

Return the overlap coefficient for two `Text` values. Returned value is in the range from 0 (no similarity) to 1 (exact match). Return 1 if both `Text` values are empty.

See also: https://en.wikipedia.org/wiki/Overlap_coefficient.

Since: 0.3.0

jaccard :: Text -> Text -> Ratio Int Source #

Return the Jaccard similarity coefficient for two `Text` values. Returned value is in the range from 0 (no similarity) to 1 (exact match). Return 1 if both

See also: https://en.wikipedia.org/wiki/Jaccard_index

Since: 0.3.0

# Other

hamming :: Text -> Text -> Maybe Int Source #

O(n) Return the Hamming distance between two `Text` values. Hamming distance is defined as the number of positions at which the corresponding symbols are different. The input `Text` values should be of equal length or `Nothing` will be returned.

See also: https://en.wikipedia.org/wiki/Hamming_distance.

Heads up, before version 0.3.0 this function returned ``Maybe` `Natural``.

jaro :: Text -> Text -> Ratio Int Source #

Return the Jaro distance between two `Text` values. Returned value is in the range from 0 (no similarity) to 1 (exact match).

While the algorithm is pretty clear for artificial examples (like those from the linked Wikipedia article), for arbitrary strings, it may be hard to decide which of two strings should be considered as one having “reference” order of characters (order of matching characters in an essential part of the definition of the algorithm). This makes us consider the first string the “reference” string (with correct order of characters). Thus generally,

    jaro a b ≠ jaro b a

This asymmetry can be found in all implementations of the algorithm on the internet, AFAIK.

See also: https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance

Heads up, before version 0.3.0 this function returned ``Ratio` `Natural``.

Since: 0.2.0

jaroWinkler :: Text -> Text -> Ratio Int Source #

Return the Jaro-Winkler distance between two `Text` values. Returned value is in range from 0 (no similarity) to 1 (exact match).

See also: https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance

Heads up, before version 0.3.0 this function returned ``Ratio` `Natural``.

Since: 0.2.0