When using nested documents and the Apache Solr Block Join functionality it is a common requirement to query for an entity (for example the parent entity) and then retrieve for each search result all(or some of) the related children. Let's see the most important aspects of such functionality and how to apply complex queries when … Continue reading Apache Solr ChildDocTransformerFactory: How to Build Complex ChildFilter Queries
London Information Retrieval Meetup June
After the very warm reception of the first edition, the second London Information Retrieval Meetup is approaching (25/06/2019) 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-june-tickets-62261343354Our first speaker is René Kriegler, freelance search consultant and search engineer : René Kriegler René has … Continue reading London Information Retrieval Meetup June
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
London Information Retrieval Meetup
The London Information Retrieval Meetup is approaching (19/02/2019) and we are excited to add more details about the speakers and talks!The event is free and you are invited to register :https://www.eventbrite.com/e/information-retrieval-meetup-tickets-54542417840After Sambhav Kothari, software engineer at Bloomberg and Elia Porciani, R&D software engineer at Sease, our last speaker is Andrea Gazzarini, founder and software engineer at Sease … Continue reading London Information Retrieval Meetup
Rated Ranking Evaluator: Help the poor (Search Engineer)
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