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.

About Jaccard similarity

Word-token Jaccard index between two texts—optional case folding, in your browser. The interactive transform on this page runs in your browser tab—Toolcore does not need your paste for the core operation described above.

How to use this page

Paste or type in the main workspace, run the primary action from the toolbar, then copy or download the result. Use Load example when the page offers it, or URL prefill (?q= / ?qb=) so agents and tickets open the same input.

Jaccard similarity: 50.0%

Nearby workflows on Toolcore

  • Hamming distance — Count differing positions between two equal-length strings—Hamming distance calculator in your browser. for the next text or markup step in your edit loop.
  • Levenshtein distance — Compare two strings for edit distance and similarity score—local Levenshtein calculator. for the next text or markup step in your edit loop.
  • Anagram checker — Compare two strings for anagrams—optional ignore case and spaces—sorted letter match in your browser. for the next text or markup step in your edit loop.
  • Character frequency — Count how often each character appears—sorted table with Unicode code points; local only. for the next text or markup step in your edit loop.

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.

More tools

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