AI engineering glossary · RAG vector search
What is sparse retrieval?
Sparse retrieval: Retrieval based on sparse term-weight vectors, where most entries are zero and each nonzero entry stands for a word or subword. Classic examples use inverted indexes with BM25; learned sparse models also exist. It excels at exact terms and rare names.
Sparse retrieval: an example
A search for the error code 'ERR_4031' finds the one page containing that exact string.
Related terms
More RAG vector search terms
- Structure-aware chunking
- Synthetic test set
- Table extraction
- Text extraction
- Top-k retrieval
- Two-stage retrieval
- Vector database
- Vector index
Where you learn it
Sparse retrieval is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.