Search Relevance

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.

 Scaling late interaction models in Elasticsearch - part 2
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.

Understanding sparse vector embeddings with trained ML models

Understanding sparse vector embeddings with trained ML models

Learn about sparse vector embeddings, understand what they do/mean, and how to implement semantic search with them.

How to search languages with compound words

January 29, 2025

How to search languages with compound words

Compound words present challenges in search engines during text analysis and tokenization, as they can obscure meaningful connections between word components. Tools like the Hyphenation Decompounder Token Filter help address these issues by deconstructing compound words.

Improve search results by calibrating model scoring in Elasticsearch

December 23, 2024

Improve search results by calibrating model scoring in Elasticsearch

Learn how to leverage annotated data to calibrate semantic model scoring for better search results

Query rules retriever: ensuring business rules work seamlessly with semantic search

December 19, 2024

Query rules retriever: ensuring business rules work seamlessly with semantic search

Harness the power of Elasticsearch query rules combined with semantic search and rerankeras.

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