Online Optimization of Video-Ad Allocation

Online Optimization of Video-Ad Allocation

Hanna Sumita, Yasushi Kawase, Sumio Fujita, Takuro Fukunaga

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 423-429. https://doi.org/10.24963/ijcai.2017/60

In this paper, we study the video advertising in the context of internet advertising. Video advertising is a rapidly growing industry, but its computational aspects have not yet been investigated. A difference between video advertising and traditional display advertising is that the former requires more time to be viewed. In contrast to a traditional display advertisement, a video advertisement has no influence over a user unless the user watches it for a certain amount of time. Previous studies have not considered the length of video advertisements, and time spent by users to watch them. Motivated by this observation, we formulate a new online optimization problem for optimizing the allocation of video advertisements, and we develop a nearly (1 − 1/e)-competitive algorithm for finding an envy-free allocation of video advertisements.
Keywords:
Agent-based and Multi-agent Systems: Economic paradigms, auctions and market-based systems
Combinatorial & Heuristic Search: Combinatorial search/optimisation