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Glossary

Hybrid Retrieval

Hybrid retrieval combine semantic vector search with lexical keyword search to retrieve relevant passages. Vector search capture meaning and paraphrase, keyword search capture exact terms and identifiers, and fusion step merge both result sets so precise tokens and conceptual matches no dey missed.

Synonym dem: hybrid search, dense-sparse retrieval, vector plus keyword search, fusion retrieval

Hybrid retrieval acknowledge say no single retrieval signal enough for production quality. Dense vector embeddings excel at conceptual similarity but blur exact identifiers; sparse lexical methods nail precise tokens but ignore meaning. By running both and fusing their rankings, hybrid retrieval improve recall without sacrificing precision, which matter when answer must be grounded in exactly di right passage. Reranking pass over fused candidates then sharpen final context handed to di model.

Question dem wey people dey ask well-well

Why combine vector and keyword search?
Vector search fit miss rare exact terms like SKUs or error codes, while keyword search miss paraphrases. Fusing both recover di strengths of each and raise recall on real-world queries.
How di two result sets dey combined?
Fusion method like reciprocal rank fusion or weighted score blend rerank merged candidates, often followed by cross-encoder reranker for final precision.