With advanced tools available for search like Solr and Elasticsearch, companies are embedding search in almost all their products and websites. WIth more experienced users but also with smaller screens to show search results, returned the right results to a query becomes more demanding. Search engines provide lots of ways to influence the order of the search results by changing your query. Besides that you have the option to extend them with plugins to teach the search engines new tricks. One new trick is called “learning to rank”. Learning to rank uses a machine learned model to come up with a better ranking of the search results. During the presentation you’ll learn what Learning To Rank is. To be able to understand the machine learning part, you get information about machine learning models, feature extraction and the training of models. You will also learn about when to apply learning to rank and of course you’ll get an example to show how it works using elasticsearch and a learning to rank plugin. After this presentation you have learned how and why to combine Machine Learning and Search.
As a software developer/architect I have always looked for new technologies that can be combined with things I have been using for a while. It started out with embedding specific tools/frameworks into the spring framework. After that, I started embedding charting libraries in angular and react applications. These days I am working a lot with elasticsearch. I am mostly doing relevance tuning. Some time ago, I starting learning about machine learning. My logical step is then to combine these two. Meet Learning To Rank. That is my main focus for the past year, how to get good search analytics and how to use these to improve the search results.
Byron Voorbach is a Search & Data engineer at Luminis in Amsterdam. He has broad experience in security, backend development and Spring technologies. For the last 5 years, Byron has mostly been working with the Elastic Stack, taking a great interest in building and optimizing search engines. He loves to go to music festivals and travel in his spare time.