A video monetization system and method are disclosed to run an auction to maximize the revenue from a sequence of multiple video ads, while minimizing the impact on the user's watch time. The system uses two predictive models, implemented with a machine learning algorithm that also takes into account user behavior/history. The method uses whole-commercial session features like the number of ads shown, the length of each ad, and the sequence of ads for selecting optimal commercial breaks to display to a user. Online video platforms may use full-session auction to optimize the entire sequence of video ads that they show within commercial breaks, in order to maximize revenue effectively.
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Toksoz, Tuna and Price, Thomas, "Full-Session Auction For Video Ads", Technical Disclosure Commons, (March 01, 2017)