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Vocabulary

Understand the term. Connect the concept.

A practical dictionary of 512 AI, machine learning, mathematics, and programming terms from HerbDev’s AI Vocabulary app. Start with a definition, explore an example, then follow the concepts behind it.

Linked concepts open in a new tab. Audio reads the definition and example.

Cosine Similarity

Embeddings & Vector Search · Level 3 of 5

Cosine Similarity

The dot product of nonzero vectors divided by the product of their lengths.

It measures directional alignment and ignores overall magnitude.

Example

Two normalized text vectors receive a high similarity score.

Listen to the definition and example

Audio transcript

Cosine Similarity. The dot product of nonzero vectors divided by the product of their lengths. It measures directional alignment and ignores overall magnitude. For example: Two normalized text vectors receive a high similarity score.

Explore this concept

A useful analogy

Comparing which way two arrows point, regardless of their lengths.

Why it matters

This helps you understand why a retrieval system finds or misses related information.

Technical detail

cos(a,b) = (a·b)/(||a||₂ ||b||₂), defined for nonzero vectors. Unit-normalized vectors reduce this to a dot product.

Common misconception

Cosine similarity is undefined for zero vectors and is not always between zero and one.

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Related concepts

Quick recall question

Try answering before looking back at the definition.

Put the terminology into context: How AI works · Machine-native representations · All learning paths

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