I-Corps: AdsProphet: Full-screen Delay-aware Mobile Ads Display

I-Corps：AdsProphet：全屏延迟感知移动广告显示

• 批准号: 1558209
• 负责人: Yan Chen
• 金额: $ 5万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1558209&HistoricalAwards=false
• 关键词: Corps; AdsProphet; Full; screen; Delay; Corps; AdsProphet; Full; screen; Delay

Mobile advertising is a large and quickly growing market, driven by the movement of viewing traffic and advertising dollars from other media to mobile. In 2014, mobile worldwide ad spending is about $40 billion and it's expected to top nearly $200 billion in 2019. Among all the hundreds of thousands of app developers operating today, 90% of which offer free apps that create revenues through "in-app" advertising: they get paid when a user clicks on an ad embedded in their apps. Nowadays, these app developers have to play banner ad in their apps, which is a small-sized ad form that usually runs at the bottom of the screen, attracting littler user attentionand thus reducing developers' revenues. The proposed technology "AdsProphet" is a novel mobile ads library that is based on the observation that when user using apps, a lot of time has been wasted on waiting for the app to load remote data and such 'freezing time' has not been fully taken advantage of. AdsProphet can find these valuable windows and displays full-screen ads, which attracts user attention 25 times higher than what banner ads can achieve. This I-Corps team assumes app developers can use AdsProphet to display full-screen ads at a rate of 10% of banner ads, then AdsProphet is expected to double developers' revenue without affecting user experiences.The key technique behind AdsProphet is a novel real-time user-perceived delay prediction system on mobile device. It's challenging to propose such a system: first, during each networking delay,only a portion of it is user-perceived delay when user can do nothing but to wait. There is no built-in event for it in any systems. This I-Corps team proposes a novel approach that is able to intelligentlydetect user-perceived delay by combing techniques of network behavior manipulation, image similarity comparison algorithms and user behavior model. Second, the networking condition varies dramatically and frequently on a mobile device: users move their phones from place to place and connect to different networks such as WIFI or cellular network all the time. Moreover, the prediction process must decide whether or not to play ads in real-time; otherwise, it wastes the time to play full-screen ads and affect developers? revenues. The team first proposes an approach to predict user-perceived delay by designing a novel algorithm to efficiently estimate bandwidth aswell as round trip time to target servers, both of which serve as the most essential indicators of current networking condition. Then, to further accelerate the proposed prediction system, the team proposes a networking history model based on user's history.

移动广告是一个大型迅速增长的市场，这是由于观看流量和广告资金从其他媒体到移动设备的发展。 2014年，移动全球广告支出约为400亿美元，预计在2019年将近2000亿美元。在当今运营的所有成千上万的应用程序开发人员中，其中90％提供了免费的应用程序，这些应用程序通过“应用程序内”广告创造收入：当用户点击其应用程序中的广告时，它们会得到付费。如今，这些应用程序开发人员必须在其应用程序中播放横幅广告，这是一种通常在屏幕底部运行的小型广告表单，吸引了Littler用户的注意力，从而减少了开发人员的收入。提出的技术“ ADSPROPHET”是一个新颖的移动广告库，基于这样的观察，即当用户使用应用程序时，在等待该应用程序加载远程数据时，已经浪费了很多时间，而这种“冻结时间”尚未完全利用。 AdsProphet可以找到这些有价值的窗口并显示全屏广告，该广告吸引了用户注意力比横幅广告所能达到的25倍。该I-Corps团队假设应用程序开发人员可以使用AdsProphet以横幅广告的10％的速度显示全屏广告，那么Adsprophet预计将使开发人员的收入增加一倍，而不会影响用户体验。AdsProphet背后的关键技术是一种新颖的实时用户在移动设备上的实时用户延迟预测系统。提出这样的系统是一项挑战：首先，在每个网络延迟期间，只有一部分是用户感知到的延迟，而用户除了等待时无能为力。在任何系统中都没有内置事件。这个I-Corps团队提出了一种新颖的方法，能够通过梳理网络行为操纵技术，图像相似性比较算法和用户行为模型来智能地探索用户感知的延迟。其次，网络条件在移动设备上频繁而频繁地变化：用户在一个地方将手机移动并连接到不同网络，例如WiFi或Cellular Network等不同的网络。此外，预测过程必须决定是否实时播放广告。否则，它会浪费时间播放全屏广告并影响开发人员？收入。该团队首先提出了一种方法，通过设计一种新颖的算法来预测用户感知到的延迟，以有效估计带宽以及往返时间到目标服务器的往返时间，这两者都是当前网络条件的最重要的指标。然后，为了进一步加速提出的预测系统，团队根据用户的历史记录提出了一个网络历史模型。