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Length Normalization

The mathematical process of scaling embedding vectors to a unit length (magnitude of 1) so that retrieval is based purely on the angular direction of vectors. In RAG pipelines, this ensures that Cosine Similarity can be computed as a simple Dot Product, preventing long documents or high-frequency term clusters from disproportionately influencing retrieval scores.

Definition

The mathematical process of scaling embedding vectors to a unit length (magnitude of 1) so that retrieval is based purely on the angular direction of vectors. In RAG pipelines, this ensures that Cosine Similarity can be computed as a simple Dot Product, preventing long documents or high-frequency term clusters from disproportionately influencing retrieval scores.

Disambiguation

Distinguish from 'Token Truncation' or 'Text Cleaning'; this refers to vector magnitude in latent space.

Visual Metaphor

"A Compass Needle: regardless of how long the needle is physically, only the direction it points matters for navigation."

Key Tools
NumPyFAISSPineconePyTorchscikit-learn
Related Connections

Conceptual Overview

The mathematical process of scaling embedding vectors to a unit length (magnitude of 1) so that retrieval is based purely on the angular direction of vectors. In RAG pipelines, this ensures that Cosine Similarity can be computed as a simple Dot Product, preventing long documents or high-frequency term clusters from disproportionately influencing retrieval scores.

Disambiguation

Distinguish from 'Token Truncation' or 'Text Cleaning'; this refers to vector magnitude in latent space.

Visual Analog

A Compass Needle: regardless of how long the needle is physically, only the direction it points matters for navigation.

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