Machine Learning for optimizing search results with Drupal & Apache Solr

Nick Veenhof

Nick Veenhof is CTO at Dropsolid and is leading the technical team there in combination with the R&D team. Nick has been involved in the Drupal Open Source community for over 12 years but touched a lot more technologies than just that, such as cloud infrastructure and devops philosophies. Aside of technology, He tries to be a good mentor for the Scrum Masters and Technical Architects by embracing change and to lead by example.

He is also advocating Open Source and especially the Open Source project Drupal. That software crossed his path during his studies and took up a significant part of his career when he started to use it for professional purposes in several Drupal-focussed development agencies.

Presentation Description

In this session I'll give you a summary of what machine learning is but more importantly how can you use it for a very common problem, namely the relevancy of your internal site search.

Recently, a client of ours shared with us their frustration that their website’s internal site search results didn’t display the most relevant items when searching for certain keywords. They had done their homework and provided us with a list of over 150 keywords and the expected corresponding search result performance. I'll take you on a roadshow how complex Search is and why we all came to rely on Google and came to expect similar quality from our other searches online. 

You'll leave the session with a general understanding of not only machine learning concepts but also how search works and how you can use the toolkit of Solr/Lucene to improve your site search with minimal impact for your Drupal site. I'll try to keep it understandable for all audiences but do expect a high level of technical content and concepts.