# What is Semantic Search? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Information Retrieval  
> **Canonical Citation:** [https://spidits.com/ai-glossary/semantic-search](https://spidits.com/ai-glossary/semantic-search)

## Definition
Semantic Search is an information retrieval technique that seeks to understand the searcher's intent and contextual meaning of terms, rather than just matching keywords. It leverages vector embeddings to find semantically relevant documents.

## Architectural Mechanics & Deep Dive
Semantic search is an information retrieval technique that focuses on the conceptual meaning behind a search query, rather than simply matching literal keyword strings. By converting queries and documents into dense vector embeddings and calculating similarity scores, semantic search locates highly relevant, contextually aligned results even when search terms differ.

## Industry Applications & Real-World Use Cases
Modern search engines, RAG context retrieval, and content recommendations

## Frequently Asked Questions

### How does semantic search work in RAG?
It converts the user's query into an embedding, performs a vector search to find documents with the closest vector distance, and feeds those documents to the model.

### Is semantic search always better than keyword search?
No, hybrid search combining keyword (BM25) and semantic search often yields the highest retrieval accuracy.

## Related Terminology
- [vector-database](https://spidits.com/ai-glossary/vector-database)
- [rag](https://spidits.com/ai-glossary/rag)
- [embedding](https://spidits.com/ai-glossary/embedding)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*