Web Summit Uses Neo4j For Innovative Conference Support

neo4j

Leading Tech Conference Organiser Web Summit Implements a Recommendation System Using neo4j to Scale Their Events past 100,000 Attendees

World-leading tech conference organiser Web Summit is using graph technology software from Neo4j, the #1 platform for connected data, to improve attendee experience across all its international conferences.

Web Summit’s conferences are supported by a powerful and scalable app, designed to help the company expand their events and help attendees network. Underlying this unique app is Neo4j, which allowed Web Summit to quickly and easily deploy and extend the advanced algorithms that power best-in-industry event recommendations. These recommendations ensure attendees make the best connections at and get the most out of their time at the conferences.

Evan O'Brien
Evan O’Brien

For Web Summit software engineer Evan O’Brien, “Our conferences enable the best possible networking opportunities for our attendees, and there’s no better way to represent a network than with a graph.”

Web Summit’s lead data scientist, Steven Tobin, says graph database Neo4j is the best way to model such relationships: “Neo4j is a perfect fit for our approach to conferences, letting us model and leverage attendees’ existing relationships and all their interactions during the conferences in real time.”

O’Brien adds, “Neo4j’s technology not only makes what we do possible, it also makes it scalable.”

Emil Eifrem
Emil Eifrem

Neo4j’s CEO Emil Eifrem is set to present ‘The past, present and future of graphs and connected data,’ at the upcoming Lisbon Web Summit (November 8, Binate.io stage, 11.40am-12.00pm). Emil will cover the state of the graph database landscape, the power of connecting data, people, systems and things and the popular graph use cases with real-life examples ranging from space engineering with NASA to the Panama Papers investigatory journalism. Attendees will also hear his thoughts on the future of graph technology and its position in emerging use cases such as machine learning and AI.

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