Anna Ruggero Main Blog

Explaining Learning to Rank Models with Tree Shap

Introduction A common problem with machine learning models is their interpretability and explainability.We create a dataset and we train a model to achieve a task, then we would like to understand how the model obtains those results. This is often quite difficult to understand, especially with very complex models. In this blog post, I would … Continue reading Explaining Learning to Rank Models with Tree Shap

Alessandro Benedetti Evaluation & User Behaviour, Learning To Rank, Machine Learning, Main Blog, Meetup

London Information Retrieval Meetup June

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

Anna Ruggero Learning To Rank, Machine Learning, Main Blog, Search

Online Testing for Learning To Rank: Interleaving

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

Anna Ruggero Learning To Rank, Machine Learning, Main Blog, Search

The Importance of Online Testing in Learning to Rank – Part 1

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

Alessandro Benedetti Apache Lucene, Apache Solr, Elasticsearch, Main Blog, Synonyms

Introducing Weighted Synonyms in Apache Lucene/Solr

This blog post is about our latest contribution to the Apache Lucene/Solr project:introducing the ability of assigning different weights to synonyms.This contribution aims to help users that deal with complex synonyms dictionaries where it's important to associate a numerical weight to each of them, for example to boost the ones that are more important in … Continue reading Introducing Weighted Synonyms in Apache Lucene/Solr

Alessandro Benedetti Apache Lucene, Apache Solr, Elasticsearch, Information Retrieval, Main Blog, Meetup

London Information Retrieval Meetup February

After the very warm reception of the first year, the fourth London Information Retrieval Meetup is approaching (11/02/2020) and we are excited to add more details about our speakers and talks!The event is free and you are invited to register : https://www.eventbrite.com/e/london-information-retrieval-meetup-february-2020-tickets-89056738101 Our first speaker is Anna Ruggero, one of our R&D software engineers: Anna … Continue reading London Information Retrieval Meetup February

Alessandro Benedetti Apache Lucene, Apache Solr, Elasticsearch, Main Blog, RRE

Road to Rated Ranking Evaluator Enterprise

It was the spring of 2018, Andrea was strenuously working on a customer project, continuously tuning search configurations and checking the ground truth for certain queries manually. That was pretty much the standard at the time, the brilliant Quepid[1] from our friends at Open Source Connection helped in some use cases, but there was nothing … Continue reading Road to Rated Ranking Evaluator Enterprise