A Software Engineer is always required to give his customers a concrete evidence about deliverables quality. A Search Engineer deals with a specialisation of such generic Software Quality, which is called Search Quality. What is Search Quality? And why is it so important in a search infrastructure? After all, the "Software Quality" should be omni-comprensive, … Continue reading Rated Ranking Evaluator: Help the poor (Search Engineer)
Apache Lucene BlendedInfixSuggester : How It Works, Bugs And Improvements
The Apache Lucene/Solr suggesters are important to Sease : we explored the topic in the past[1] and we strongly believe the autocomplete feature to be vital for a lot of search applications. This blog post explores in details the current status of the Lucene BlendedInfixSuggester, some bugs of the most recent version ( with the … Continue reading Apache Lucene BlendedInfixSuggester : How It Works, Bugs And Improvements
Apache Solr: orchestrating Known item and Full-text search
Scenario You’re working as a search engineer for XYZ Ltd, a company which sells electric components. XYZ provided you the application logs of the last six months, and some business requirements. Two kinds of customers, two kinds of requirements, two kinds of search The log analysis shows that XYZ has mainly two kinds of customers: … Continue reading Apache Solr: orchestrating Known item and Full-text search
Give the height the right weight: quantities detection in Apache Solr
Quantity detection? What is a quantity? And why do we need to detect it? A quantity, as described by Martin Fowler in his "Analysis Patterns" [1] is defined as a pair which combines an amount and unit (such as 30 litres, 0.25 cl, or 140 cm). In search-based applications, there are many cases where you may … Continue reading Give the height the right weight: quantities detection in Apache Solr
ECIR 2018 Experience
This blog is a quick summary of my (subjective) experience at ECIR 2018 : the 40th European Conference on Information Retrieval, hosted in Grenoble (France) from 26/03/2018 to 29/03/2018. Deep Learning and Explicability Eight long papers accepted were about Deep Learning. The topics "Neural Network" and "Word Embedding" were the most occurring in the accepted … Continue reading ECIR 2018 Experience
Solr Is Learning To Rank Better – Part 4 – Solr Integration
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 … Continue reading Solr Is Learning To Rank Better – Part 4 – Solr Integration
Solr Is Learning To Rank Better – Part 3 – Ltr tools
Apache Solr Learning to Rank - Things Get Serious This blog post is about the Apache Solr Learning to Rank Tools : a set of tools to ease the utilisation of the Apache Solr Learning To Rank integration. The model has been trained in Part 2, we are ready to deploy it to Solr, but … Continue reading Solr Is Learning To Rank Better – Part 3 – Ltr tools
Solr Is Learning To Rank Better – Part 2 – Model Training
Model Training For Apache Solr Learning To Rank If you want to train a model for Apache Solr Learning To Rank , you are in the right place. This blog post is about the model training phase for the Apache Solr Learning To Rank integration. We modelled our dataset, we collected the data and refined it … Continue reading Solr Is Learning To Rank Better – Part 2 – Model Training
Solr Is Learning To Rank Better – Part 1 – Data Collection
Learning To Rank In Apache Solr Introduction This blog post is about the journey necessary to bring Learning To Rank In Apache Solr search engines. Learning to Rank[1] is the application of Machine Learning in the construction of ranking models for Information Retrieval systems. Introducing supervised learning from user behaviour and signals can improve the relevancy … Continue reading Solr Is Learning To Rank Better – Part 1 – Data Collection
Exploring Solr Internals : The Lucene Inverted Index
Introduction This blog post is about the Lucene Inverted Index and how Apache Solr internally works. When playing with Solr systems, understanding and properly configuring the underline Lucene Index is fundamental to deeply control your search. With a better knowledge of how the index looks like and how each component is used, you … Continue reading Exploring Solr Internals : The Lucene Inverted Index