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 give a better understanding of Docvalues and stored fields in Apache Solr for the operations in which they can be used interchangeably.
In this post we describe 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.
In this final part of the Entity Search with Graph Embeddings serie we see evaluation measures and results.
Entity Search: how to build virtual documents leveraging on graph embeddings. How to exploit entity embeddings and clustering.
This blog is a quick summary of my (subjective) experience at Haystack 2019 : the Search Relevance Conference, hosted in Charlottesville (Virginia, USA) from 24/04/2019 to 25/04/2019.References to the slides will be updated as soon as they become available. First of all my feedback on the Haystack Conference is extremely positive.From my perspective the conference…
How faceting is calculated in Apache Solr distributed architectures. It presents inner details explanation and practical examples.
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