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Relative CTRs at different positions in random learning bucket

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A few action-interpretation-based approaches including user segmentation, user engagement and position bias. The success of user segmentation for personalization is due to the fact that the proposed clustering algorithms actually group users by interests and preferences that are implicitly demonstrated by their behaviors. Once the interest patterns are determined by clustering algorithms, a user will be assigned to a segment by her profile features. Fortunately, user profile features also highly correlate with behaviors and interests. The user segment assignment is usually reliable except when the user is new to the site so that her profile features are poor. A few important topics towards exploring user action interpretation for online personalized content optimization. We build a online personalized content optimization system using the parallel-serving-buckets framework. In this framework, we introduce action interpretation for both more effective user segmentation and better understanding on the informativeness of different user actions. In particular, we leverage users’ click actions to group homogeneous users into the same segment; then, we explore the effects of a couple types of user engagement factors as well as the position bias on the online learning procedure. Largescale evaluations on both offline data set and online traffic of a commercial portal website demonstrate that we can significantly improve the performance of content optimization by integrating all of these user action interpretation factors into the learning process. the Internet, which has become an important medium to deliver digital content to Web users instantaneously. Digital content publishers, including portal websites, such as MSN (http:// msn.com/) and Yahoo! (http://yahoo.com/), and homepages of news media, like CNN (http://cnn.com/) and the New York Times (http://nytimes.com/), have all started providing Web users with a wide range of modules of Web content in a timely fashion.There are various specific content modules on the Yahoo! portal, such as Today module presenting today’s emerging events, News module presenting news of various aspects, and Trending Now module presenting trending queries from a search engine that is used in the portal website.