Query Expansion
Query Expansion is the process of broadening or reformulating a user query by adding related terms, synonyms, or semantically similar concepts to improve retrieval accuracy. In AI search systems, expansion helps match user intent to a wider range of relevant content embeddings.
Why It Matters
Query expansion increases retrieval recall, ensuring AI systems consider a broader and more semantically aligned content set before ranking and synthesis.
How It Works
AI systems generate related semantic variations of the original query, compare them against indexed vector embeddings, and retrieve passages that may not match exact phrasing but are contextually relevant.
Use Cases
- Improving semantic search coverage
- Enhancing RAG retrieval accuracy
- Optimizing conversational AI responses
- Reducing missed citation opportunities
Best Practices
- Cover related entities and synonyms in content
- Build semantic depth within topic clusters
- Use natural language variations in headings
- Optimize content for concept coverage, not repetition
Frequently Asked Questions
Is query expansion the same as keyword stuffing? +
Do AI systems automatically expand queries? +
How can brands benefit from query expansion? +
Related Terms
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