Powering Content Discovery Through Scalable, Realtime Profiling Of Users' Content Preferences

RECSYS(2016)

引用 3|浏览41
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摘要
Outbrain is the Web's leading content discovery service, recommending billions of stories daily to a global audience across many of the world's most prestigious and respected publishers. Outbrain's recommendation technology combines contextual cues with personalization, where the personalization aspects are a combination of content-based and collaborative filtering techniques.This paper, and the accompanying demo, offer a behind the-scenes view of the content-based aspects of Outbrain's personalization technology. We detail the types of features we extract from content, as well as the attributes we keep in each user's content-affinity profile. We then describe and demonstrate how we update each user's profile, in real time, as the user consumes content while browsing the Web.
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关键词
User Profile,Content-Based Recommendation Systems,Personalization
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