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You are here: Home / Featured Stories / Computational Advertising: The Ultimate Match-Making Challenge

Computational Advertising: The Ultimate Match-Making Challenge

January 1, 2010 Leave a Comment


Bob Bell of AT&T Labs Research talks about aspects of the Netflix competition.
Daniel Ford of Google describes optimal refresh rates for search engine indexes of web sites.

Computational advertising is defining new and highly profitable enterprises. The workshop made it clear that there are challenges amenable to straightforward statistical thinking and more challenges that demand fundamental new research. The corporate players recognize this; they have gotten great value from the computer science community and hope to reap similar rewards from engagement with statisticians.

Copies of some of the presentations are available in the past events section of the NISS web site.

The workshop was presented under the auspices of the NISS Affiliates Program and organized by Agarwal, David Banks of Duke University, and Alan Karr of NISS, who think computational advertising poses many exciting opportunities for statistical research.

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Filed Under: Featured Stories Tagged With: advertising, computational advertising, Google, Microsoft, search engines, Yahoo

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