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

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

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

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 3 – Documents and retrieval

In this post we want to get to the heart of the process of virtual documents creation. As we explained in Part 1, these documents are essential for the retrieval phase and for its performances. This part of the pipeline is, indeed, the one where we create our own approaches in many different versions. Summarizing … Continue reading Entity Search with graph embeddings – Part 3 – Documents and retrieval

Entity Search with graph embeddings – Part 2 – Embeddings and clustering

Let's continue our journey into this entity search thesis! In Part 1 we have described what entities and entity search are. We have explained how this search is implemented in the state-of-the-art. We have also introduced the new approach of this dissertation specifying also the dataset and the test collection used. Finally we have described … Continue reading Entity Search with graph embeddings – Part 2 – Embeddings and clustering

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

London Information Retrieval Meetup October

After the very warm reception of the first and second edition, the third London Information Retrieval Meetup is approaching (21/10/2019) 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-october-tickets-74403100677 Our second speaker is Andrea Gazzarini, our founder and software engineer: … Continue reading London Information Retrieval Meetup October