
OpenSearch Neural Search Plugin Tutorial
This blog post explores the new OpenSearch neural search plugin, given a detailed description of it through our end-to-end experience.

This blog post explores the new OpenSearch neural search plugin, given a detailed description of it through our end-to-end experience.

In this blog post we present the available learning to rank Apache Solr features with a focus on categorical features and how to manage them.

DeepImpact is a new document term-weighting scheme suitable for efficient sparse retrieval using a standard inverted index.

This blog post explores the internals of Apache Solr queryResultCache and filterCache through practical code examples.

Learning about text ranking using Deep Learning with BERT transformer. From training to neural re-ranking, with code snippets and examples.

How does Artificial Intelligence impact Search? This post explores the state of the art of AI applied to Information Retrieval in Open Source.

This blog post aims to illustrate step by step a Learning to Rank project on a Daily Song Ranking problem using open source libraries.

Explainability and Interpretability of Learning To Rank models are vital in Information Retrieval, in this blog we present Tree SHAP.

This blog post aims to explain Docvalues and Store fields in Apache Solr for operations in which they can be used interchangeably.

An approach to solve the problem of an application that requires both Full and Atomic Updates, using one of the powerful concepts in Object Oriented Programming: Polymorphism.
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.
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