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Saturday, April 25 • 11:10am - 11:30am
Large Scale Topic Assignment on Multiple Social Networks

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Interests and expertise is a challenging problem with applications in various data-powered products. In this talk, we present a full production system used at Lithium Technologies (Klout), which mines topical interests and expertise from multiple social networks and assigns over 10,000 topics to hundreds of millions of users on a daily basis.

The system generates a diverse set of features derived from signals such as user generated posts and profiles, user reactions such as comments and retweets, user attributions such as lists, tags and endorsements, as well as signals based on social graph connections. We show that using cross-network information with a diverse features for a user leads to a more complete and accurate understanding of the user's topics, as compared to using any single network or any single source.


Speakers
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Adithya Rao

Lithium
@AdithyaRao | Adithya is the Lead Research Engineer in the Data Science team at Lithium technologies. Some of the projects he has worked on includes the Klout score, topic extraction, user targeting and social content discovery. Before his current role, he graduated with a Masters degree from Stanford University, specializing in Machine Learning. 
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Nemanja Spasojevic

Lithium
@sofronije | Nemanja is the Director of Data Science at Lithium Technologies, and leads all the data science and engineering efforts around building scalable systems for topical text mining, user scoring and content relevance. Prior to his current role, he was previously at Google for 6 years, working on projects such as Google Books. 


Saturday April 25, 2015 11:10am - 11:30am
Theater

Attendees (21)