Research on the Frequency Capping Issue in RTB Advertising: A Computational Experiment Approach
Qin, Rui; Yuan, Yong; Wang, Fei-Yue; Li, Juanjuan; Rui Qin
2015-11
Conference Name2015 Chinese Automation Congress (CAC 2015)
Source PublicationProceedings of 2015 Chinese Automation Congress
Conference DateNov. 27-29, 2015
Conference PlaceWuhan, China
AbstractReal time bidding (RTB) is emerged with the rapid development and integration of Internet and big data, and it has become the most important business model for online computational advertising. In RTB-based advertising markets, Demand Side Platforms (DSPs) aim to help the advertisers buy ad impressions matched with their target audiences. Due to the existence of discount rate, the advertising effect may be diminished when displaying the advertisements multiple times to the same target audience. As such, frequency capping is widely considered as a crucial issue faced by most advertisers. In this paper, we mainly consider the frequency capping problems in RTB advertising markets, and establish a two-stage optimization model for advertisers and DSPs. Utilizing the computational experiment approach, we design two experiments to validate our model. The experimental results show that under different discount rates, the optimal frequency caps are different. Moreover, when considering all the discount rates, there exists an optimal frequency cap, at which the expected maximum revenue can be obtained in the long run.
KeywordReal Time Bidding Computational Advertising Frequency Capping Computational Experiment Approach Demand Side Platforms
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11568
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorRui Qin
Recommended Citation
GB/T 7714
Qin, Rui,Yuan, Yong,Wang, Fei-Yue,et al. Research on the Frequency Capping Issue in RTB Advertising: A Computational Experiment Approach[C],2015.
Files in This Item: Download All
File Name/Size DocType Version Access License
qin.pdf(2961KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Qin, Rui]'s Articles
[Yuan, Yong]'s Articles
[Wang, Fei-Yue]'s Articles
Baidu academic
Similar articles in Baidu academic
[Qin, Rui]'s Articles
[Yuan, Yong]'s Articles
[Wang, Fei-Yue]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Qin, Rui]'s Articles
[Yuan, Yong]'s Articles
[Wang, Fei-Yue]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: qin.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.