Online Optimization of Video-Ad Allocation
Hanna Sumita (NII), Yasushi Kawase (TITech), Sumio Fujita, Takuro Fukunaga (NII)
IJCAI 2017, 2017/8
データサイエンス (Data Science)
- 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.
Online Optimization of Video-Ad Allocation（外部サイト／External Site Link）