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Dot Product Similarity

A mathematical scoring method used in vector databases to calculate the alignment and magnitude between a query embedding and document embeddings. In RAG pipelines, it serves as a similarity metric where higher values indicate stronger semantic relevance, particularly when the embedding model uses magnitude to encode importance or frequency.

Definition

A mathematical scoring method used in vector databases to calculate the alignment and magnitude between a query embedding and document embeddings. In RAG pipelines, it serves as a similarity metric where higher values indicate stronger semantic relevance, particularly when the embedding model uses magnitude to encode importance or frequency.

Disambiguation

Measures both direction and magnitude, whereas Cosine Similarity only measures the angle.

Visual Metaphor

"Solar Intensity: The total energy received depends on both the angle of the sun (alignment) and the raw brightness of the source (magnitude)."

Key Tools
FAISSPineconeMilvusWeaviateNumPyPyTorch
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Conceptual Overview

A mathematical scoring method used in vector databases to calculate the alignment and magnitude between a query embedding and document embeddings. In RAG pipelines, it serves as a similarity metric where higher values indicate stronger semantic relevance, particularly when the embedding model uses magnitude to encode importance or frequency.

Disambiguation

Measures both direction and magnitude, whereas Cosine Similarity only measures the angle.

Visual Analog

Solar Intensity: The total energy received depends on both the angle of the sun (alignment) and the raw brightness of the source (magnitude).

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