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Reranking

Turkish equivalent: Yeniden sıralamaDomain: Information Retrieval

A second-stage retrieval step that applies a more expensive relevance model to reorder a smaller candidate set produced by an initial search.

Information-Retrieval Context

Reranking applies a more expensive relevance function to a smaller candidate set returned by the initial retriever. Cross-encoders, late-interaction models, or domain-specific scoring can improve top-k precision after candidate generation.

Retrieval Boundary

A reranker cannot recover a relevant document that the first-stage retriever never supplied. Its latency and quality must therefore be evaluated together with candidate-set recall.

Related technical article: Artificial Intelligence: Philosophy, Theory and Practice.

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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.