k-nearest neighbor (kNN) search

edit

k-nearest neighbor (kNN) search

edit

A k-nearest neighbor (kNN) search finds the k nearest vectors to a query vector, as measured by a similarity metric.

Common use cases for kNN include:

  • Relevance ranking based on natural language processing (NLP) algorithms
  • Product recommendations and recommendation engines
  • Similarity search for images or videos

Learn more in the Elasticsearch core documentation.

Check out our hands-on tutorial to learn how to ingest dense vector embeddings into Elasticsearch.