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

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.

Exceptions — ArgumentException when the two lengths need a (len(a) + 2) × (len(b) + 2) table larger than the largest array .NET allocates, about 46 000 characters on each side.

Example — the same pair as above, read the other way round.

using Lodestar.Text.Distances;

double s = DamerauLevenshtein.NormalizedSimilarity("MARTHA", "MARHTA");   // => 0.8333…

Remarks — use this rather than NormalizedDistance wherever a bigger number ought to mean a better match: ranking candidates, sorting descending, or handing a score to something that expects one. Nothing else about the two differs.

The trap is the empty case. NormalizedDistance("", "") is 0, so this returns 1 — two empty strings are reported as a perfect match. If an empty string means "this field was never filled in", that is exactly backwards, and the filtering has to happen before the call.

Applies to — net10.0, netstandard2.0.

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