In this session we'll build a recommendation engine from scratch while paying particular attention to the modelling choices made along the way. The data and use-cases will come from meetup.com's social gatherings.

We want to provide recommendations to attendees for finding interesting topics, groups to join and events to attend. For organizers it should help them find non-competing, optimal schedules, optimize their events and find potential members to reach out to.

We will import the data from meetup.com into our graph model and run Neo4j's Cypher graph queries to compute the content-based and collaborative filtering recommendations in real time. While doing that we'll observe how changes in the data affect the outcomes and which scores contribute to better results.

This session should provide you with enough hands-on knowledge to get started with Neo4j to import and query your own data for fun and profit.