DOT_PRODUCT
Dot product. NOTE: this similarity is intended as an optimized way to perform cosine similarity. In order to use it, all vectors must be normalized, including both document and query vectors. Using dot product with vectors that are not normalized can result in errors or poor search results. Floating point vectors must be normalized to be of unit length, while byte vectors should simply all have the same norm.
Properties
Functions
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Calculates a similarity score between the two vectors with a specified function. Higher similarity scores correspond to closer vectors. Each (signed) byte represents a vector dimension.
Calculates a similarity score between the two vectors with a specified function. Higher similarity scores correspond to closer vectors.