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Near-duplicate clustering over a dataset, with blocking so it does not compare everything to everything.

public static class Deduplicator

Example — four records, two pairs.

using Lodestar.Fuzzy;

string[] records = ["apple pie", "appel pie", "banana bread", "banana bred"];

IReadOnlyList<IReadOnlyList<int>> clusters = Deduplicator.FindClusters(
    records, record => record[..1], (a, b) => Fuzz.Ratio(a, b), threshold: 80);

int found = clusters.Count;  // => 2

Remarks — comparing every pair is n², which is fine for a thousand records and impossible for a million. Blocking is the way out: records sharing a key are compared, records that do not are never considered at all.

That makes the key the whole performance question, and the whole correctness risk. Too coarse and nothing is saved; too fine and true duplicates land in different blocks and are never compared. A first letter, as above, is a demonstration rather than a recommendation.

Applies to — net10.0, netstandard2.0.

See also — Deduplicator.FindClusters, Fuzz.