Keyword or semantic search: how to choose
Keyword search and semantic search address needs that can complement one another. Keyword search helps locate terms present in content; semantic search tries to connect a query’s intent with the meaning of documents.
Your choice should start with actual questions. You do not need to replace a search that works just because another technique sounds more sophisticated.
Start with two different requests
Imagine a support collection containing manuals and error codes. “Error ZX-14” asks for a specific match, while “I cannot finish registering” may need an explanation written with different words.
These queries deserve different tests. A system that handles broad phrases well may struggle with identifiers that must be preserved exactly.
| Fictional query | What to assess first |
|---|---|
| ZX-14 | Matching the code |
| Registration will not finish | Intent and relevant procedure |
| Version 2.1 of the manual | Identifier and version |
| How to correct my details | Meaning and context |
Microsoft’s hybrid search documentation describes combining textual and vector retrieval. It also identifies scenarios where codes and specialized terms benefit from keyword matching.
1. Build a small question collection
Gather representative queries and record which documents would be relevant. Include common spelling mistakes, synonyms and questions the collection cannot answer.
Do not rely only on examples that repeat file titles. Tests should reflect how somebody would actually look for the information.
You might start with ten or fifteen queries. That number is an exercise suggestion, not a sample size guaranteeing statistical quality for every system.
2. Compare results using the same criteria
Run the strategies against the same collection and inspect the first positions. Record whether the required document appears, its version is correct and the user is permitted to access it.
A technique does not win by returning more results. The aim is to bring useful evidence for that question, with little noise and no content inappropriate to the access context.
Save the expected documents before comparing approaches. Otherwise, it is easy to reinterpret success around whichever result happens to appear.
3. Use meaning without losing details
Vector representations can help when a query and document use different vocabulary. Similarity still does not guarantee that a passage contains the condition or exception needed.
Check names, codes, dates and limits in the source itself. A document about another product version may look close while being operationally unsuitable.
If the concept is new to you, read what embeddings are before interpreting similarity scores.
4. Assess a combination when needed
Hybrid search combines signals from different strategies. Its usefulness must be tested with the same questions rather than assumed to be superior in every situation.
Help review these search results.
For each query, inspect the expected documents and the returned results.
Classify them as relevant, partly relevant or irrelevant.
Explain using the content while preserving codes and versions.
Do not decide which strategy is better without comparing identical queries.This review can support analysis, but it does not replace inspecting documents. If the AI receives titles alone, make clear that it cannot assess conditions contained in the body text.
5. Choose for the task you want to improve
A small collection may work well with straightforward text search. Another may need paraphrase recognition, filtering and combined methods.
Document the examples each strategy helps and the operational work required to maintain it. When retrieval supplies AI answers, also review how RAG works.
Frequently asked questions
When should I assess keyword search?
When exact terms, identifiers, names or versions matter. Test whether it finds the documents needed for actual queries.
When can semantic search help?
It can help when users and documents use different words for related ideas. Results still need checking against the retrieved content.
Is hybrid search always better?
Do not assume so. Compare strategies on the same collection and questions, using consistent relevance and operational criteria.