Data Preparation Archives

December 18, 2020December 18, 2020 Ilaria Petreti Data Preparation, data science, Feature Engineering, Information Retrieval, Learning To Rank, Machine Learning, Main Blog, Search

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.

March 25, 2020May 4, 2020 Elia Porciani Apache Lucene, Apache Solr, Data Preparation, facet, faceting, Indexing, Indexing options, Information Retrieval, Lucene index, Main Blog, Search, Solr schema

DocValues VS Stored Fields : Apache Solr Features and Performance SmackDown

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.

January 28, 2020January 29, 2020 Andrea Gazzarini Apache Solr, Data Preparation, Indexing, Information Retrieval, Main Blog, Search, Solr schema, SolrJ

Apache Solr Atomic Updates: a Polymorphic Approach

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.

July 25, 2016May 14, 2018 Alessandro Benedetti Apache Solr, Data Preparation, Feature Engineering, Learning To Rank, Machine Learning, Main Blog, RankLib, Search, Signal Processing

Solr Is Learning To Rank Better – Part 1 – Data Collection

Learning To Rank In Apache Solr Introduction This blog post is about the journey necessary to bring Learning To Rank In Apache Solr search engines. Learning to Rank[1] is the application of Machine Learning in the construction of ranking models for Information Retrieval systems. Introducing supervised learning from user behaviour and signals can improve the relevancy … Continue reading Solr Is Learning To Rank Better – Part 1 – Data Collection