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Hybrid Search

Turkish equivalent: Hibrit aramaDomain: Information Retrieval

A retrieval strategy that combines lexical and semantic signals, such as BM25 and vector similarity, to improve recall and relevance.

Information-Retrieval Context

Hybrid search combines lexical and semantic retrieval signals. Sparse methods such as BM25 preserve exact terms, identifiers, and code tokens, while embedding search captures semantic similarity; rank fusion or a learned reranker can combine their complementary evidence.

Score Boundary

Raw sparse and dense scores generally do not share a meaningful scale. Simply adding them can be unstable, so normalization, rank fusion, or an explicitly trained combination method should be evaluated.

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Related concepts

Information Retrieval

Related technical publications

Publications whose title or summary directly references this concept.

Retrieval-Augmented Generation (RAG)

A production-oriented RAG course covering retrieval, hybrid search, reranking, big-data ingestion, private-data chat, Graph RAG, temporal relationship analysis, security, evaluation, and on-premises architectures.