Lexical and semantic search with Elasticsearch
In this blog, we'll explore various approaches to retrieving information using Elasticsearch, focusing on lexical and semantic search.
Multilingual vector search with the E5 embedding model
Here's how multilingual vector search works and how to use Elasticsearch with the multilingual E5 embedding model, including examples.
Adding passage vector search to Lucene
Here's how to add passage vectors to Lucene, the benefits of doing so and how existing Lucene structures can be used to create an efficient retrieval experience.
Searching by music: Leveraging vector search for audio information retrieval
Want to find out how to apply vector search to music data? In this post, we combine audio embeddings, information retrieval, machine learning, vector databases, and audio data to deliver new and exciting possibilities!
Vector search in Elasticsearch: The rationale behind the design
In this blog, you'll learn how vector search has been integrated into Elasticsearch and the trade-offs that we made.
Exploring vector databases: how to get the best of lexical and AI-powered search with Elastic’s vector database
Learn about the concepts related to vector databases, how they work and how to get the best out of lexical & AI search with Elastic’s vector database.
Enhancing chatbot capabilities with NLP and vector search in Elasticsearch
Explore how vector search and NLP work to enhance chatbot capabilities and see how Elasticsearch facilitates the process.
Text similarity search with vector fields
This post explores how text embeddings and Elasticsearch’s new dense_vector type could be used to support similarity search.