The luceneMatchVersion Parameter in Apache Solr
This blog explores how the luceneMatchVersion parameter in the solrconfig.xml works in Apache Solr. Dos and don’ts, and anything in between.
Alessandro Benedetti
April 21, 2021
A Learning to Rank Project on a Daily Song Ranking Problem – Part 3
This blog post aims to illustrate how to generate the query Id and how to manage the creation of the Training Set
Ilaria Petreti
March 25, 2021
Common Errors with Apache Solr Feature and Model Stores
Common errors and warnings in manipulating feature stores and models in Solr. Pay attention also to JVM Heap and Zookeeper.
Anna Ruggero
March 8, 2021
London Information Retrieval Meetup (March 2021)
Join our London Information Retrieval Meetup online, for a free evening meetup aimed to Information Retrieval passionates and professionals
Lisa Biella
March 1, 2021
Apache Solr Learning to Rank Feature Stores and Models
How to list, upload, delete feature stores and models necessary in Solr for learning to rank.
Anna Ruggero
February 25, 2021
A Learning to Rank Project on a Daily Song Ranking Problem – Part 2
This blog post is about several analysis on a LTR model and its explanation using the open source library SHAP
Ilaria Petreti
February 15, 2021
Elasticsearch _source, doc_values and store Performance
In this blog post, the elasticsearch _source field is compared with stored fields and docvalues from a performance point of view
Elia Porciani
February 1, 2021
Sease at Chorus 2021
Info about speakers and talk at the Chorus Workshop conference 2021 at Plain Schwarz.
Lisa Biella
January 26, 2021
Offline Search Quality Evaluation: Rated Ranking Evaluator (RRE)
The Rated Ranking Evaluator (RRE) is an offline search quality evaluation library for both Apache Solr and Elasticsearch.
Alessandro Benedetti
January 11, 2021
A Learning to Rank Project on a Daily Song Ranking Problem
This blog post aims to illustrate step by step a Learning to Rank project on a Daily Song Ranking problem using open source libraries.
Ilaria Petreti
December 18, 2020
We are Sease, an Information Retrieval Company based in London, focused on providing R&D project guidance and implementation, Search consulting services, Training, and Search solutions using open source software like Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
