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Abstract Details
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Activity Number:
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486
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #303691 |
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Title:
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Estimating Traffic for Millions of Queries in Real Time
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Author(s):
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Tim Hesterberg*+ and Oliver Dain and Yogita Mehta and Laramie Leavitt
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Companies:
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Google and MIT Lincoln Laboratory and Google and Google
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Address:
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2628 31st Ave W, Seattle, WA, 98199, United States
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Keywords:
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Online learning ;
Poisson regression ;
updating ;
web traffic ;
spike detection ;
online algorithm
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Abstract:
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Google estimates traffic for millions of queries continuously. This is used for many applications, such as caching results for frequent queries, and looking for spikes. We describe how Google efficiently processes a wide variety of queries with frequencies ranging from tens to millions of hits per day, with widely varying activity across time of day and week, and updates these models continuously as new data is observed.
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Authors who are presenting talks have a * after their name.
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