In this blog post we present the available learning to rank Apache Solr features with a focus on categorical features and how to manage them.
How the FeatureLogger works? When the Feature Vector Cache is used in Solr? Is the cache speeding up the rerank process?
How a learning to rank query works in Solr? How we can obtain the required features extraction time from the Solr qTime parameter?
This blog post is about several analysis on a LTR model and its explanation using the open source library SHAP
This blog post aims to illustrate step by step a Learning to Rank project on a Daily Song Ranking problem using open source libraries.
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…
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…
This blog is a quick summary of our experience at the ECIR 2018, the European Conference on Information Retrieval.
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 are ready to…
This blog post is about the Apache Solr Learning to Rank Tools : a set of utilities for the Solr LTR integration.