Elasticsearch _source, doc_values and store Performance

In this blogpost I want to explore what possibilities elasticsearch gives us for storing fields and retrieve them at query time from the performance point of view. In fact, lucene, the underlying library upon which elasticsearch and solr are built, provides two ways for storing and retrieving fields: stored fields and docvalues. In addition, elasticsearch … Continue reading Elasticsearch _source, doc_values and store Performance

Offline Search Quality Evaluation: Rated Ranking Evaluator (RRE)

Introduction With Rated Ranking Evaluator Enterprise approaching soon, we take the occasion of explaining in details why Offline Search Quality Evaluation is so important nowadays and what you can do already with the Rated Ranking Evaluator open-source libraries. More news will come soon as we are approaching the V1 release date. Stay tuned! Search Quality … Continue reading Offline Search Quality Evaluation: Rated Ranking Evaluator (RRE)

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

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

Entity Search with graph embeddings – Part 4 – Evaluation and conclusion

This is the last post of the Entity Search with graph embeddings serie. In Part 2 and Part 3 we illustrated the core of the dissertation describing in detail the implementation of our solution pipeline. In this final part we will see some evaluation measures and results. We will draw some conclusions explaining which were … Continue reading Entity Search with graph embeddings – Part 4 – Evaluation and conclusion

Entity Search with graph embeddings – Part 1 – Overview

This series of blog posts wants to describe my master degree dissertation done with the supervision of Prof. Gianmaria Silvello at the University of Padova. The main focus of this project is in the use of graph embeddings in order to create virtual documents for the Information Retrieval Entity Search task. This thesis description is … Continue reading Entity Search with graph embeddings – Part 1 – Overview

Haystack 2019 Experience

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 … Continue reading Haystack 2019 Experience