Jaccard similarity

Client

Compare how much two texts overlap by unique words—intersection over union from 0% to 100%. For edit distance instead of set overlap, try Levenshtein distance.

What Jaccard measures

Jaccard similarity is the size of the word intersection divided by the size of the word union—reported here from 0% to 100%. It ignores word order, so two sentences with the same unique tokens score 100% even when phrasing differs.

When to pick another metric

Use Levenshtein distance when typos and insertions matter, or Sørensen–Dice and token sort ratio when you want overlap coefficients tuned for short labels or fuzzy dedupe.

Jaccard similarity: 50.0%

Nearby workflows on Toolcore

Common use cases

  • Estimate keyword overlap between two short descriptions or tags.
  • Sanity-check duplicate content before deeper NLP pipelines.

Common mistakes to avoid

  • Treating it like edit distance

    Jaccard ignores word order—reordered sentences can still score 100%.

FAQ

How are words tokenized?

Text is split on whitespace; edge punctuation is stripped; matching is case-insensitive.

Is data uploaded?

No. Similarity is computed locally in your browser.

Common search terms

Phrases people search for that match this tool. See the full long-tail keyword index.

  • jaccard similarity calculator
  • word set similarity between texts
  • jaccard index text comparison
  • compare token overlap online

More tools

Related utilities you can open in another tab—mostly client-side.