Sparse retrieval relies on traditional keyword-matching methods to find relevant documents. It is fast and effective for exact matches — specific product codes, regulatory references, precise phrases — but less effective when users phrase queries differently from how the content is written.
In practice, sparse and dense retrieval are typically combined in hybrid search systems. Sparse retrieval handles the cases where exact terms matter — compliance codes, product names, specific identifiers. Semantic search handles the cases where meaning matters more than wording. Together, they cover more of the real-world retrieval landscape than either approach alone.
