Find and Replace in Elasticsearch Fields
In this blog post we explore how to find and replace a specific value within a field of an Elasticsearch index.
In this blog post we explore how to find and replace a specific value within a field of an Elasticsearch index.
This blogpost describes the use cases where n-grams are useful, explain the risks of using them, and present some alternative solutions that should be considered.
This blog post gives you an overview of how fuzzy queries work in Elasticsearch with examples and references.
This blog post explores how to index Elasticsearch documents from a JSON file using Python API, specifically the Bulk Helpers
The goal of this blog post is to highlight new vector search capabilities introduced in version 8.8.0, especially ESRE
This ‘tips and tricks’ describes the steps to follow to compare models on common queries in online search quality evaluation
This blog post describes an alternative and customized approach for evaluating ranking models through the use of Kibana.
This blog post showcases the vector search improvements that have been introduced in the latest versions of Elasticsearch (8.6 and 8.7)
This blog post describes an alternative and customized approach for evaluating ranking models through the use of Kibana.
This blog post explains all the steps required to implement Text Embedding and Vector Search directly in Elasticsearch in a very simple way.
We are Sease, an Information Retrieval Company based in London, focused on providing R&D project guidance and implementation, Search consulting services, Training, and Search solutions using open source software like Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
Follow our newsletter to stay
updated on Information Retrieval news, events and promotions!
WhatsApp us