BM25
A classic lexical ranking function. Still used as a first-stage retriever before fancy embeddings.
If your page never uses the words the user used, BM25 might not retrieve you even if you are “semantically close.”
Put the real product nouns on the page. Not stuffing. Presence.
Examples
- Users say “SOC 2.” Your page only says “trust program.” Sparse retrieval skips you; a dense retriever might still find you. Don’t rely on one.
Related terms
Vectors that represent meaning. They power semantic search and RAG. Your page becomes a point in space.
Combining keyword (BM25) and vector retrieval. Many RAG stacks do this. Your nouns and your meaning both count.
RAG means the model looks up documents at answer time instead of relying only on what it memorized in training.
FAQ
Should I keyword stuff? +
No. Use the terms practitioners use, once, in the section that answers the question.
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