Similarity Search
Definition
Similarity search finds objects that lie particularly close to each other according to a defined comparison measure.
Similarity search finds the objects nearest to a query according to a defined distance or similarity function.
Simply explained
You provide an example, and the search finds things similar to it according to the chosen metric.
Why it matters in practice
The term improves reliable access to data and knowledge as well as their usable linkage in digital systems.
Example from business
A knowledge system finds semantically similar document sections for a support question.
Limits and pitfalls
- Metric, embedding, and index must fit the use case; unchecked approximation can omit relevant hits.
Origin & history
Efficient nearest neighbor methods range from spatial indexes to approximate nearest neighbor libraries like FAISS.
Use in mid-sized companies
- Possible application: A knowledge system finds semantically similar document sections for a support question.
Frequently asked questions
What does similarity search mean?
Similarity search finds the objects nearest to a query according to a defined distance or similarity function. What should you watch out for? Metric, embedding, and index must fit the use case; unchecked approximation can omit relevant hits.
Sources
- Billion-scale similarity search with GPUs · Johnson et al., Billion-scale similarity search with GPUs
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: