Query expansion improves retrieval by rewriting a vague user query into more specific terms or related subqueries. In a RAG system, this shifts retrieval from the user’s raw wording toward the information they actually need. section 7.3.3
From broad question to targeted retrieval
Instead of searching only for “What trends should we be aware of in AI?”, the system can generate “What are the latest trends in AI for SaaS platforms?” and “What AI developments are impacting workflow automation?” These focused queries retrieve more relevant material. section 7.3.3
Expansion can work alongside query transformation and query classification. Classification routes questions about technical advances, market trends, or product integration through retrieval pipelines with different source priorities. section 7.3.3

