| Document Date: 2013-09-02 22:30:25
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City Melville / New York / / Company LinkedIn / Personalized Web Content Optimization Systems / ACM Inc. / Yahoo! / Microsoft / CNN / the New York Times / / Country United States / / Currency USD / / / Facility Penn Plaza / University of California / / / IndustryTerm news media / Web content optimization problems / straightforward graph-based algorithm / Web portals / online recommendation / Web content / Web users / ONLINE CONTENT RECOMMENDATION Content modules / Digital content publishers / conventional recommendation algorithms / online learning schemes / Online Learning / Web portal content optimization problem / portal services / online learning framework / Web portal services / real time / online process / computational advertising / Web content optimization / Online vs. Batch / online learning algorithms / Web portal / real-world commercial recommender systems / recommender systems / et al. mendation algorithm / state-of-theart online learning framework / Web publishers / Web content optimization system / Web content optimization problem / Web content optimization using preferences / recommendation algorithm / search applications / Web portal content optimization / generative algorithm / Web content optimization yield / Web-based services General Terms / online learning setting / search queries / online learning methodology / online learning algorithm / Internet users / search query / search engine / search results / Web Content Optimization Systems / learning-torank algorithm / learning algorithms / / Movie How to deal / / Organization University of California / IDF / / / Position model / and personalization / Web-based services General / representative / / ProvinceOrState California / New York / / PublishedMedium the New York Times / / Technology 6 J. Bian et al. mendation algorithm / search engine / machine learning / straightforward graph-based algorithm / pairwise learning algorithms / two specific algorithms / two algorithms / recommendation algorithm / online learning algorithm / pairwise learning-torank algorithm / formalized Bayesian generative algorithm / two specified algorithms / online learning algorithms / conventional recommendation algorithms / / URL http /
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Exploiting User Preference for Online Learning in Web Content Optimization Systems JIANG BIAN, Microsoft Research BO LONG, LinkedIn LIHONG LI, Microsoft Research TAESUP MOON, University of California at Berkerley