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

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.

Programme of the seventh London Information Retrieval Meetup. Save the date: 10 December 2020 at 6 PM. It is free and online!

In this post we describe what is an Intervals Table and how to build it using a Behaviour-Driven-Development (BDD) approach.

Secrets of Interleaving approaches for Learning To Rank online testing/evaluation. It includes implementation details and pro/cons analysis.

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

In this post we describe what is an Intervals Table and how to build it using a Behaviour-Driven-Development (BDD) approach.

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.

Let’s quickly setup a Solr development environment for implementation and debugging purposes, with our 5 minutes how to!

Third part of the journey into Entity Search trough embeddings. Focus of the post is the ranking phase.
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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