Search relevance is a hard problem. Satisfying the user information needs across a multitude of different factors and business requirements may seem daunting, but do not despair! This Search Relevance Training teaches you how to design, develop, and configure your open source search engine to maximize how well the search results fit the user information need. Join us as we explore the milestones of search relevance to the deep internals of Apache Lucene/Solr. Exercises and war stories from real-world problems and solutions are included.
Would you like to schedule a training for your Team?
Our trainings are meant for different targets (business, developer and everything in between),
and are individual/small groups/classroom-based.
We offer different levels of flexibility to make sure the training course will be a perfect fit for your requirements:
ON SITE OR REMOTE
LIVE OR RECORDED
FROM BEGINNER TO EXPERT
Skills You Will Gain
• Deep understanding of how query-matching work;s
• Deep understanding of how search result ranking works;
• Capacity of customizing and tuning your system relevance function;
• Better debugging/troubleshooting ability;
• How to measure the search quality of your engine.
• Familiarity with search engine technologies;
• Familiarity with Apache Lucene/Solr.
Technical Managers, Technical Leads, Software Engineers, Developers, Information Retrieval Passionates.
APACHE LUCENE/SOLR COMMITTER
Alessandro has been involved in designing and developing search-relevant solutions from the early stages of Apache Solr 1.4 and edismax query parser in 2010. Over the years he has worked on various projects aiming to build search solutions able to satisfy the user information needs, often integrating such solutions with machine learning and artificial intelligence technologies.
Andrea Gazzarini is a curious software engineer, mainly focused on the Java language and Search technologies. With more than 15 years of experience in various software engineering areas, his adventure in the search world began in 2010, when he met Apache Solr and later Elasticsearch.
- Introduction on Information Retrieval and Lucene/Solr technologies
- The Apache Lucene/Solr Index
- Apache Lucene/Solr field analysis: the schema.xml
- Apache Lucene scoring and document similarity
- Debug Query deep dive
- Apache Solr query parsers (with a focus on the dismax and edismax)
- Field centric vs term centric approach
- Disjunction max vs Boolean approach (and everything in the middle)
- Function Queries
- Additive and Multiplicative boost functions and queries
- Distributed search relevance considerations
- Search Quality Evaluation: how to test your relevance
- Learning to Rank: a machine learning approach for relevance
- Language Modelling and vector-based search: the neural approach to relevance
- Search Relevance War Stories