Cosine Similarity
Cosine Similarity is a mathematical metric used to measure the similarity between two vectors in high-dimensional space by calculating the cosine of the angle between them. It is independent of vector magnitude, focusing purely on direction.
Frequently Asked Questions
What is the range of cosine similarity?▼
Between -1 and 1. In text embedding searches, the value is typically between 0 (orthogonal, unrelated) and 1 (aligned, identical semantic meaning).
Why is cosine similarity preferred over Euclidean distance?▼
Euclidean distance is sensitive to vector length (e.g. document length), whereas cosine similarity measures semantic alignment regardless of length.
Quick Facts
- CategoryMathematical Foundations
- Key ApplicationVector search queries, semantic clustering, and RAG document matching
Coverage Trend12 Weeks
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