Mining the Eventbrite Social Graph for Recommending Events

Vipul Sharma (Eventbrite)
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Recommendation systems have become critical for delivering relevant and personalized content to your users. Such systems not only drive revenues and generate significant user engagement for web companies but also are a great discovery tool for users. Facebook’s newsfeed, Linkedin’s people you may know and Eventbrite’s event recommendations are some great examples of recommendation systems.

During this talk we will share the architecture and design of Eventbrite’s data platform and recommendation engine. We will describe how we mined a massive social graph of 18M users and 6B first degree connections to provide relevant event recommendations. We will provide details of our data platform, which supports processing more than 2 TB social graph data daily. We intent to describe how Hadoop is becoming the most important tool to do data mining and also discuss how machine learning is changing in presence of Hadoop and big data.

We hope to provide enough details that folks can learn from our experiences while building their data platform and recommendation systems.

Photo of Vipul Sharma

Vipul Sharma


Vipul Sharma is leading the data discovery group at Eventbrite where he and his team is working on problems like data platforms, recommendation systems, search, social graph mining etc

Before that Vipul had been working on web big data problems for quite a while now. He has spent over many years fighting spam using machine learning and big data.


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