Main blog
Welcome to our Main Blog, the cornerstone of our exploration into information retrieval. This dedicated space serves as a comprehensive repository where we delve into our research, findings, and various topics predominantly centered around information retrieval.
Apache Solr Learning To Rank Feature Extraction and qTime
How a learning to rank query works in Solr? How we can obtain the required features extraction time from the Solr qTime parameter?
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.
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.
A Learning to Rank Project on a Daily Song Ranking Problem – Part 4
Query-level features and under-sampled queries, how to handle them? Find it out, with our new Learning to Rank implementations
Apache Solr sow Parameter (Split on Whitespace) and Multi-Field Full-Text Search
This blog post explores the Apache Solr multi-field search limitations with a focus on the sow(split on whitespace) parameter.
A Learning to Rank Project on a Daily Song Ranking Problem – Part 3
This blog post aims to illustrate how to generate the query Id and how to manage the creation of the Training Set
A Learning to Rank Project on a Daily Song Ranking Problem – Part 2
This blog post is about several analysis on a LTR model and its explanation using the open source library SHAP
Elasticsearch _source, doc_values and store Performance
In this blog post, the elasticsearch _source field is compared with stored fields and docvalues from a performance point of view
Offline Search Quality Evaluation: Rated Ranking Evaluator (RRE)
The Rated Ranking Evaluator (RRE) is an offline search quality evaluation library for both Apache Solr and Elasticsearch.
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.
Apache Solr Learning To Rank Interleaving
Interleaving is an online evaluation approach for ranking functions, contributed to Apache Solr Learning to Rank by Sease.
Music Information Retrieval: the Intervals Matrix
In this post we describe what is an Intervals Table and how to build it using a Behaviour-Driven-Development (BDD) approach.
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.
Online Testing for Learning To Rank: Interleaving
Secrets of Interleaving approaches for Learning To Rank online testing/evaluation. It includes implementation details and pro/cons analysis.
The Importance of Online Testing in Learning to Rank – Part 1
It is fundamental to online test your Learning To Rank system, this blog shows you how it can be implemented and the most common mistakes.
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.
Introducing Weighted Synonyms in Apache Lucene/Solr
This blog post is about our latest contribution to the Apache Lucene project: introducing weighted synonyms to provide better query expansion.
Music Information Retrieval: the Intervals Table
In this post we describe what is an Intervals Table and how to build it using a Behaviour-Driven-Development (BDD) approach.