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Abstract Details
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Activity Number:
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144
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Type:
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Invited
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #300384 |
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Title:
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Large Scale Data at Facebook
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Author(s):
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Eric Sun*+
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Companies:
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Facebook, Inc.
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Address:
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, , ,
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Keywords:
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Facebook ;
entities ;
social networks ;
crowdsourcing ;
large-scale
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Abstract:
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In this talk we share lessons about user behavior gained from the analysis of aggregated status updates, check-ins, and Like data from the 750 million active users on Facebook. In particular, we focus on how user behavior has influenced the growth and curation of the graph of Facebook Community Pages. Community Pages represent concepts can be added to users' profiles on Facebook, allowing them to express their passions and share their interests with others. With hundreds of millions of Pages, problems like deduplication and disambiguation quickly become computationally difficult. We propose several solutions for these problems that can be applied at Facebook's scale, including cleaning up the graph via statistical algorithms and integrating user feedback via crowdsourcing.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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