It divides their dot product by the product of their lengths, producing a normalized similarity score. Retrieval systems often use it when embedding direction carries the relevant semantic signal.
Cosine similarity compares vectors by the angle between them rather than their raw magnitude.
It divides their dot product by the product of their lengths, producing a normalized similarity score. Retrieval systems often use it when embedding direction carries the relevant semantic signal.