What is cosine similarity?

Cosine similarity measures the angle between two TF-IDF word vectors. A score of 100% means identical word distributions; 0% means no words in common.

What is Jaccard similarity?

Jaccard similarity is the size of the word-set intersection divided by the size of the union. It focuses on vocabulary overlap regardless of word frequency.

What does Levenshtein distance measure?

Levenshtein (edit) distance counts the minimum number of single-character insertions, deletions, or substitutions needed to turn one text into the other.

Which metric should I use?

Use cosine for long documents, Jaccard for short keyword-based comparisons, and Levenshtein for short strings where character-level differences matter.

Text 無料サインアップ不要

Text Similarity Calculator

Measure how similar two texts are using cosine, Jaccard, and Levenshtein metrics.

ツールを読み込み中…

このツールについて

Paste two pieces of text and calculate three complementary similarity metrics: cosine similarity on TF-IDF word vectors (ideal for comparing documents), Jaccard similarity on word sets (measures vocabulary overlap), and Levenshtein distance at the character level (useful for near-duplicate strings). Results include a percentage score for each metric, the list of shared words, and words unique to each text — helping you decide how alike two documents truly are.

使い方

1 Paste the first text into the left text area.
2 Paste the second text into the right text area.
3 Click Compare to compute all three similarity metrics.
4 Review the percentage scores, shared words, and unique words panels.

このツールについて

使い方

よくある質問