Text Cosine Similarity Calculator

Calculate cosine similarity of texts

Cosine similarity measures the angle between two vectors, and in text analysis those vectors are the word-frequency counts of two documents. This calculator builds a term-frequency vector for each text and computes the cosine of the angle between them, which ranges from zero, meaning no shared words, to one, meaning identical word distributions. It is the classic measure of how similar two pieces of text are by content.

Because it compares the direction of the vectors rather than their length, cosine similarity is unaffected by document length, so a short and a long text about the same topic can still score highly.

From word counts to semantic search

Cosine similarity on term frequencies is the foundation of classic information retrieval and search ranking, and the same cosine measure applied to embedding vectors powers modern semantic search and retrieval-augmented generation. Understanding the term-frequency version builds intuition for how similarity scoring works before embeddings are involved. The dot product and shared-term count shown here reveal how the score is formed.

For meaning beyond exact word matches, embedding-based cosine similarity captures synonyms and context that this term-frequency version cannot. All calculation happens locally in your browser.

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