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Hybrid Search: Why Single-Mode Search Fails in RAG

Keyword search (BM25) finds exact term matches but misses synonyms and meaning. Semantic search (vectors) understands meaning but misses exact terms, acronyms, and proper nouns. Hybrid search combines both for dramatically better retrieval quality.

How Hybrid Search Works

  1. Query runs through both BM25 keyword index and vector similarity search
  2. Results from both are merged using Reciprocal Rank Fusion (RRF) or weighted scoring
  3. A reranker (cross-encoder model) reorders the combined results by relevance
  4. Top results are passed to the LLM as context

Learn Hybrid Retrieval

Module 7 covers hybrid search, reranking, query expansion, and Graph RAG.

How to Use This Topic

This page is a focused entry point into the larger course. Use it to understand the vocabulary, the production problem, and the first practical module to open next.

  • Read the overview to map the concept to real engineering work.
  • Follow the linked module for exercises, diagrams, and implementation details.
  • Return to the full curriculum when you need adjacent topics and a complete learning path.

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