Have Neural Networks Killed the Inverted Index?
DeepImpact is a new document term-weighting scheme suitable for efficient sparse retrieval using a standard inverted index.
Antonio Mallia
April 28, 2022
QueryResultCache and FilterCache in Apache Solr
This blog post explores the internals of Apache Solr queryResultCache and filterCache through practical code examples.
Daniele Antuzi
April 14, 2022
From Training to Ranking: Using BERT to Improve Search Relevance
Learning about text ranking using Deep Learning with BERT transformer. From training to neural re-ranking, with code snippets and examples.
Antonio Mallia
December 22, 2021
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.
Alessandro Benedetti
July 7, 2021
A Learning to Rank Project on a Daily Song Ranking Problem
This blog post aims to illustrate step by step a Learning to Rank project on a Daily Song Ranking problem using open source libraries.
Ilaria Petreti
December 18, 2020
Explaining Learning to Rank Models with Tree Shap
Explainability and Interpretability of Learning To Rank models are vital in Information Retrieval, in this blog we present Tree SHAP.
Anna Ruggero
July 15, 2020
DocValues VS Stored Fields: Apache Solr Features and Performance SmackDown
This blog post aims to explain Docvalues and Store fields in Apache Solr for operations in which they can be used interchangeably.
Elia Porciani
March 25, 2020
Apache Solr Atomic Updates: a Polymorphic 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.
Andrea Gazzarini
January 28, 2020
Entity Search with graph embeddings – Part 4 – Evaluation and conclusion
In this final part of the Entity Search with Graph Embeddings serie we see evaluation measures and results.
Anna Ruggero
December 17, 2019
Entity Search with graph embeddings – Part 1 – Overview
Entity Search: how to build virtual documents leveraging on graph embeddings. How to exploit entity embeddings and clustering.
Anna Ruggero
November 14, 2019
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.
