Text levenshtein normalizedsimilarity

Development build. This page describes main, not a released package. The latest published Lodestar.Text is 0.4.0 — read its documentation.

Levenshtein.NormalizedSimilarity

1 - NormalizedDistance: 1 when the two are identical, 0 when nothing survives.

public static double NormalizedSimilarity(ReadOnlySpan<char> a, ReadOnlySpan<char> b, TextElement element = TextElement.Utf16Unit)

Parameters — a and b are the two strings to compare; element says what counts as one character, exactly as it does for NormalizedDistance, which this is computed from.

Returns — double in [0, 1], larger meaning more alike. Two empty inputs give 1.

Example — the same three edits, read as a score.

using Lodestar.Text.Distances;

double s = Levenshtein.NormalizedSimilarity("kitten", "sitting");   // => 0.5714…

Remarks — this is the member to reach for by default when you want one number saying how alike two strings are and you have no particular reason to prefer another measure. It matches Levenshtein.normalized_similarity in rapidfuzz exactly.

Two traps. Two empty inputs return 1, a perfect match between two blanks — filter empties first if that is wrong for your data. And this is not fuzz.ratio: that is Indel.NormalizedSimilarity times 100, and substituting this for it is the single most common porting mistake in this area.

Applies to — net10.0, netstandard2.0.

See also — Levenshtein.NormalizedDistance, Indel.NormalizedSimilarity, DamerauLevenshtein.NormalizedSimilarity, the Python equivalence table.