Dot-product similarity
A vector comparison affected by both direction and magnitude.
What Dot-product similarity does not show
Scores are not comparable across models or indexes without knowing how embeddings were produced and normalized.
Terms this definition uses
Related terms in Retrieval engineering
How pages become chunks, vectors and candidates inside an answer engine, and why being retrieved is not being cited.
Corpus · Document ingestion · Data connector · Parsing · OCR · Layout-aware parsing · Semantic chunking · Fixed-size chunking · Chunk overlap · Parent-child retrieval · Metadata filtering · Vector database · Vector index · Sparse vector · Dense vector · Cosine similarity · Approximate nearest neighbor · HNSW · Top-k · Retrieval recall · Retrieval precision · Mean reciprocal rank · Normalized discounted cumulative gain · Relevance score · Candidate generation · Query rewriting · Query expansion · HyDE · Multi-query retrieval · Reciprocal rank fusion · Late interaction · Lexical retrieval · Semantic search · Exact-match retrieval · Freshness boosting · Authority weighting · Source diversity · Deduplication · Near-duplicate detection · Semantic cache · Retrieval latency · Retrieval cutoff · Citation mapping · Answer synthesis
Questions about Dot-product similarity
What is Dot-product similarity?
A vector comparison affected by both direction and magnitude.
What does Dot-product similarity not show or guarantee?
Scores are not comparable across models or indexes without knowing how embeddings were produced and normalized.
Which area of the glossary does Dot-product similarity belong to?
Retrieval engineering: How pages become chunks, vectors and candidates inside an answer engine, and why being retrieved is not being cited.
← Cosine similarity · Approximate nearest neighbor →
See it in the full glossary · 731 terms across 19 areas.