Recommendation Engines: Going Beyond the Social Graph

Do your 500 "friends" on social networks really know what you will like? How many of your friends' shared links that you click each day are interesting to you? The social graph brings trust and meaning to the web, but often creates information overload from over-sharing. And because real-time updates and feeds emphasize recency over relevance, rare gems often fall through the cracks. This talk will discuss the issues and considerations when designing a personalized discovery engine, one that combines the social, peer and taste graphs to produce relevant, peer-sourced recommendations and serendipitous discovery of new online content. StumbleUpon CEO Garrett Camp will go over the concepts and mechanisms behind such recommendation systems, and highlight findings from analysis of StumbleUpon's database of over 15 billion personalized stumbles.

LEVEL: Intermediate