Online Optimization of Video-Ad Allocation
Abstract
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.
Cite
Text
Sumita et al. "Online Optimization of Video-Ad Allocation." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/60Markdown
[Sumita et al. "Online Optimization of Video-Ad Allocation." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/sumita2017ijcai-online/) doi:10.24963/IJCAI.2017/60BibTeX
@inproceedings{sumita2017ijcai-online,
title = {{Online Optimization of Video-Ad Allocation}},
author = {Sumita, Hanna and Kawase, Yasushi and Fujita, Sumio and Fukunaga, Takuro},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {423-429},
doi = {10.24963/IJCAI.2017/60},
url = {https://mlanthology.org/ijcai/2017/sumita2017ijcai-online/}
}