Statistical Challenges in Recommeder System for Web Applications

Tuesday, September 15, 2009
7:00 PM
Free and open to the public

In this talk, I will begin with an overview of statistical challenges that arise in recommender system problems for web applications like content optimization, online advertising. I will then describe some modeling solutions for a content optimization problem that arises in the context of the Yahoo! Front Page. In particular, I will discuss time series models to track item popularity, explore-exploit/sequential design schemes to enhance performance and matrix factorization models to personalize content to users. For some of the methods, I will present experimental results from an actual system at Yahoo!. I will also provide examples of other applications where the techniques are useful and end with discussion of some open problems in the area.

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Deepak Agarwal

Principal Research Scientist
Yahoo! Research