Category: AI Search & Retrieval
Definition
BM25 is a ranking algorithm used in information retrieval to estimate how relevant a document is to a search query.
It is a well-established method for keyword-based and sparse retrieval, and it considers factors such as how often query terms appear in a document and how common those terms are across the collection.
Why It Matters
BM25 is useful because exact keyword matching alone does not tell a search system which matching document is most relevant.
BM25 helps rank results by considering signals such as:
- Term frequency: how often a query term appears
- Inverse document frequency: how uncommon or informative the term is
- Document length: how long the document is compared with other documents
This allows search systems to distinguish stronger matches from weaker ones.
Example
Imagine a user searches:
“AI visibility glossary”
A retrieval system may find hundreds of documents containing the word “AI.”
A BM25-based system can give greater weight to documents that contain the important query terms in relevant ways, helping rank more useful results higher.
BM25 vs. Semantic Search
BM25 primarily evaluates relationships between the words in a query and the words in a document.
Semantic Search uses techniques such as embeddings to evaluate conceptual or meaning-based similarity.
For example, BM25 may favor a page containing the exact phrase “AI visibility”, while semantic search may also identify a page discussing visibility in generative search even without using the exact phrase.
BM25 and Hybrid Search
BM25 can be combined with dense vector retrieval in a Hybrid Search system.
A simplified architecture might look like:
Query → BM25 Retrieval + Dense Retrieval → Combined Results → Re-Ranking
This allows a system to benefit from both exact terminology and semantic similarity.
Why BM25 Matters for AI Visibility
AI visibility is increasingly associated with semantic and generative search, but traditional retrieval techniques can still play an important role in how information is discovered.
Using clear, consistent terminology can therefore remain valuable, particularly for brands, products, entities, and specialized concepts.
Related Terms
Sparse Retrieval · Keyword Search · Dense Retrieval · Hybrid Search · Relevance Scoring · Re-Ranking · Semantic Search · Retrieval
In Simple Terms
BM25 is a search-ranking algorithm that helps determine which documents are most relevant to a query based largely on the words they contain.
