Dot product similarity

Dot product similarity is a measure that multiplies two vectors element by element and sums the results. For normalized vectors it gives the same ranking as cosine similarity.

Dot product similarity sits in the Retrieval & memory part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called inner product.