BM25
Okapi BM25 is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework and improves upon TF-IDF by adding term frequency saturation and document length normalization.
Frequently Asked Questions
What is term frequency saturation in BM25?▼
It limits the impact of multiple term occurrences. If a keyword appears 20 times in a document, BM25 doesn't score it 20 times higher than if it appeared twice.
Why is BM25 still popular in the era of vector search?▼
Because keyword search is highly precise for exact matches (like serial numbers or names) where semantic embeddings might fail due to lack of keyword specificity.
Quick Facts
- CategoryInformation Retrieval
- Key ApplicationKeyword search engines, hybrid search systems, and initial candidate retrieval in RAG.
Coverage Trend12 Weeks
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