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显示广告中标题竞价的底价失败率预测

Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising
课程网址: http://videolectures.net/kdd2019_kalra_wang_borcea/  
主讲教师: Chong Wang
开课单位: 普林斯顿大学计算机科学系
开课时间: 2020-03-02
课程语种: 英语
中文简介:
到2022年,美国在线显示广告的收入预计将达到79亿美国。显示广告的一种主要方式是通过实时竞价(RTB)。在RTB中,广告交易所在多个广告商之间进行第二次价格拍卖,以出售每个广告印象。出版商通常会设定一个底价,即广告印象可以接受的最低价格。如果出价高于底价,则收入为底价和第二高出价之间的较高价格;否则,收入为零。因此,较高的储备价格可能会增加收入,但相关风险较高。在本文中,我们研究了估计储备价格失效率的问题,即储备价格未能超过报价的概率。这个问题的解决方案对出版商设置适当的储备价格以最小化风险和优化预期收入具有管理意义。由于大多数出版商不知道RTB广告商提供的历史最高投标价格,所以这个问题极具挑战性。为了解决这个问题,我们开发了一个用于储量价格失效率预测的参数生存模型。通过考虑用户和页面交互以及标头投标信息,该模型得到了进一步改进。实验结果证明了该方法的有效性。
课程简介: The revenue of online display advertising in the U.S. is projected to be 7.9 billion U.S. dollars by 2022. One main way of display advertising is through real-time bidding (RTB). In RTB, an ad exchange runs a second price auction among multiple advertisers to sell each ad impression. Publishers usually set up a reserve price, the lowest price acceptable for an ad impression. If there are bids higher than the reserve price, then the revenue is the higher price between the reserve price and the second highest bid; otherwise, the revenue is zero. Thus, a higher reserve price can potentially increase the revenue, but with higher risks associated. In this paper, we study the problem of estimating the failure rate of a reserve price, i.e., the probability that a reserve price fails to be outbid. The solution to this problem have managerial implications to publishers to set appropriate reserve prices in order to minimizes the risks and optimize the expected revenue. This problem is highly challenging since most publishers do not know the historical highest bidding prices offered by RTB advertisers. To address this problem, we develop a parametric survival model for reserve price failure rate prediction. The model is further improved by considering user and page interactions, and header bidding information. The experimental results demonstrate the effectiveness of the proposed approach.
关 键 词: 显示广告中标题竞价; 标题竞价的底价; 底价失败率预测
课程来源: 视频讲座网
数据采集: 2022-09-16:cyh
最后编审: 2022-09-19:cyh
阅读次数: 36