This blog post aims to illustrate step by step a Learning to Rank project on a Daily Song Ranking problem using open source libraries.
Interleaving is an online evaluation approach for ranking functions, contributed to Apache Solr Learning to Rank by Sease.
Join us at our sixth Information Retrieval meetup (fully remote), to explore and discuss the latest trends in the field.
After the very warm reception of the first year, the fifth London Information Retrieval Meetup is approaching (23/06/2020) and we are excited to add more details about our speakers and talks!The event is going to be fully remote (given the COVID-19 situation) and free! You are invited to register : https://www.meetup.com/London-Information-Retrieval-Meetup-Group/events/270905716/ Our second speaker is … Continue reading London Information Retrieval Meetup June
If you have read Part 1 of this blog post, you should know by now how many fantastic things can be done with online testing! In particular, the advantages that interleaving brings with respect to A/B testing, but you are still waiting for the answer to a question: how to implement it? Let's see together … Continue reading Online Testing for Learning To Rank: Interleaving
You have just trained a learning to rank model and you now want to know how it performs. You can start by looking at the evaluation parameters returned by the train on the test set, but you are still not sure of which will be the impact in using it in a real website. This … Continue reading The Importance of Online Testing in Learning to Rank – Part 1
This blog is a quick summary of my (subjective) experience at ECIR 2018 : the 40th European Conference on Information Retrieval, hosted in Grenoble (France) from 26/03/2018 to 29/03/2018. Deep Learning and Explicability Eight long papers accepted were about Deep Learning. The topics "Neural Network" and "Word Embedding" were the most occurring in the accepted … Continue reading ECIR 2018 Experience
Last Stage Of The Journey This blog post is about the Apache Solr Learning To Rank ( LTR ) integration. We modelled our dataset, we collected the data and refined it in Part 1 . Trained the model in Part 2 . Analysed and evaluate the model and training set in Part 3 . We … Continue reading Solr Is Learning To Rank Better – Part 4 – Solr Integration
Apache Solr Learning to Rank - Things Get Serious This blog post is about the Apache Solr Learning to Rank Tools : a set of tools to ease the utilisation of the Apache Solr Learning To Rank integration. The model has been trained in Part 2, we are ready to deploy it to Solr, but … Continue reading Solr Is Learning To Rank Better – Part 3 – Ltr tools
Model Training For Apache Solr Learning To Rank If you want to train a model for Apache Solr Learning To Rank , you are in the right place. This blog post is about the model training phase for the Apache Solr Learning To Rank integration. We modelled our dataset, we collected the data and refined it … Continue reading Solr Is Learning To Rank Better – Part 2 – Model Training