Semantic Search
Definition
Semantic Search is the process of retrieving information by comparing the meaning of a query with the meaning of stored content, usually through vector representations.
Key Points
- Semantic search matches intent and meaning, not just literal wording.
- It typically uses embeddings and vector databases.
- It improves recall for messy or domain-specific corpora.
- It is a core enabler of knowledge retrieval and RAG.
- Poor semantic search returns the wrong context even when the downstream model is strong.
Concept
Traditional keyword search looks for exact or near-exact term overlap. Semantic search instead uses embeddings to compare the underlying meaning of the query and the documents. That makes it more effective when the same idea can be expressed in many different ways, which is common in operational text, logs, procedures, and incident records. The result is often a better-ranked set of passages for an AI model or human operator to use.
Explainer
For ConnectedEarth, semantic search matters because operators rarely phrase questions the same way the source material phrases the answer. A maintenance note, port call instruction, or NOC incident record may contain the right information even when the wording differs from the user's query. Semantic search makes those answers retrievable in practice, which is why it sits underneath knowledge retrieval and retrieval augmented generation.
Cite this entry
Semantic Search. ConnectedEarth Knowledge Base. https://connectedearth.space/knowledge-base/semantic-search/ (updated 13 September 2026).