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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 - #300146 |
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Title:
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Statistical Plumbing: Effective use of classical statistical methods for large scale applications
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Author(s):
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Rachel Schutt*+ and Daryl Pregibon
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Companies:
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Google Inc. and Google Inc.
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Address:
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, , 10025, USA
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Keywords:
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social networks ;
large-scale ;
google ;
algorithms
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Abstract:
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Many of today's large scale applications have a lot in common with statistical applications 50 years ago. While the domains are obviously different (e.g., internet vs agriculture) and the amount of available data orders of magnitude larger, they often share the same underlying statistical model formulation. We present one such instance that is ubiquitous in the search engine industry, namely ranking. We draw on earlier work on ranking models (Bradley-Terry) and illustrate how methods devised in an earlier era are applicable today.
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