Cosine similarity
Cosine similarity normalizes a dot product by both vector norms. It compares direction rather than raw magnitude, but its relevance still depends on how the embedding space was trained.
\cos(\theta)=\frac{x\cdot y}{\lVert x\rVert\lVert y\rVert}
Overview. Cosine similarity normalizes a dot product by both vector norms.
Context. It compares direction rather than raw magnitude, but its relevance still depends on how the embedding space was trained.
Claims and evidence
Claim ledger, 2Cosine similarity normalizes a dot product by both vector norms.
It compares direction rather than raw magnitude, but its relevance still depends on how the embedding space was trained.