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Search Relevance - Elasticsearch Labs

Search Relevance

April 16, 2025

ES|QL, you know, for Search - Introducing scoring and semantic search

With Elasticsearch 8.18 and 9.0, ES|QL comes with support for scoring, semantic search and more configuration options for the match function and a new KQL function.

ES|QL, you know, for Search - Introducing scoring and semantic search
Enhancing relevance with sparse vectors

April 11, 2025

Enhancing relevance with sparse vectors

Learn how to use sparse vectors in Elasticsearch to boost relevance and personalize search results with minimal complexity.

Generating filters and facets using ML

Generating filters and facets using ML

Exploring the pros and cons of automating the creation of filters and facets in a search experience using ML models vs the classical hard-coded approach.

How to automate synonyms and upload using our Synonyms API

How to automate synonyms and upload using our Synonyms API

Discover how LLMs can be used to identify and generate synonyms automatically, allowing terms to be programmatically loaded into the Elasticsearch synonym API.

 Scaling late interaction models in Elasticsearch - part 2

Scaling late interaction models in Elasticsearch - part 2

This article explores techniques for making late interaction vectors ready for large-scale production workloads, such as reducing disk space usage and improving computation efficiency.

Searching complex documents with ColPali - part 1

Searching complex documents with ColPali - part 1

The article introduces the ColPali model, a late-interaction model that simplifies the process of searching complex documents with images and tables, and discusses its implementation in Elasticsearch.

Unifying Elastic vector database and LLM functions for intelligent query

Unifying Elastic vector database and LLM functions for intelligent query

Leverage LLM functions for query parsing and Elasticsearch search templates to translate complex user requests into structured, schema-based searches for highly accurate results.

Semantic search, leveled up: now with native match, knn and sparse_vector support

Semantic search, leveled up: now with native match, knn and sparse_vector support

Semantic text search becomes even more powerful, with native support for match, knn and sparse_vector queries. This allows us to keep the simplicity of the semantic query while offering the flexibility of the Elasticsearch query DSL.

How to build autocomplete feature on search application automatically using LLM generated terms

How to build autocomplete feature on search application automatically using LLM generated terms

Learn how to enhance your search application with an automated autocomplete feature in Elastic Cloud using LLM-generated terms for smarter, more dynamic suggestions.

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