fuzz_: Calculate similarity between two strings

In rmetaverse/synthesisr: Import, Assemble, and Deduplicate Bibliographic Datasets

Calculate similarity between two strings

Description

These functions duplicate the approach of the 'fuzzywuzzy' Python library for calculating string similarity.

Usage

fuzzdist(
  a,
  b,
  method = c("fuzz_m_ratio", "fuzz_partial_ratio", "fuzz_token_sort_ratio",
    "fuzz_token_set_ratio")
)

fuzz_m_ratio(a, b)

fuzz_partial_ratio(a, b)

fuzz_token_sort_ratio(a, b)

fuzz_token_set_ratio(a, b)

Arguments

a	A character vector of items to match to b.
b	A character vector of items to match to a.
method	The method to use for fuzzy matching.

Value

Returns a score of same length as b, giving the proportional dissimilarity between a and b.

Note

fuzz_m_ratio() is a measure of the number of letters that match between two strings. It is calculated as one minus two times the number of matched characters, divided by the number of characters in both strings.

fuzz_partial_ratio() calculates the extent to which one string is a subset of the other. If one string is a perfect subset, then this will be zero.

fuzz_token_sort_ratio() sorts the words in both strings into alphabetical order, and checks their similarity using fuzz_m_ratio().

fuzz_token_set_ratio() is similar to fuzz_token_sort_ratio(), but compares both sorted strings to each other, and to a third group made of words common to both strings. It then returns the maximum value of fuzz_m_ratio() from these comparisons.

fuzzdist() is a wrapper function, for compatability with stringdist.

Examples

fuzzdist("On the Origin of Species",
         "Of the Original Specs",
         method = "fuzz_m_ratio")

rmetaverse/synthesisr documentation built on Feb. 23, 2025, 5:29 p.m.