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1. 发明申请

US20120054027A1 NETWORK BASED ADVERTISEMENT SYSTEM 审中-公开
标题翻译：基于网络的广告系统
公开(公告)号：US20120054027A1
公开(公告)日：2012-03-01
申请号：US12871240
申请日：2010-08-30
申请人： Randolph Preston McAfee , Vijay Krishna Narayanan , Jayavel Shanmugasundaram , Rajesh G. Parekh
发明人： Randolph Preston McAfee , Vijay Krishna Narayanan , Jayavel Shanmugasundaram , Rajesh G. Parekh
IPC分类号： G06Q30/00
CPC分类号： G06Q30/0251
摘要： A network based advertisement system includes an optimizer configured to forecast a supply of opportunities, forecast a supply of guaranteed contracts, and forecast a supply of non-guaranteed contracts. Each opportunity represents a user visiting a webpage. Each guaranteed contract guarantees the matching of an advertisement to a number of opportunities. Each non-guaranteed contract guarantees a user event associated with an advertisement. The optimizer then generates a plan for matching contracts to opportunities based on the forecasted supply of opportunities, the forecasted supply of guaranteed contracts, the forecasted supply of non-guaranteed contracts, and an objective function that balances a group of parameters that define the representativeness of contracts, a cost associated with not serving non-guaranteed contracts, and performance objectives associated with contracts.
摘要翻译：基于网络的广告系统包括优化器，其被配置为预测机会供应，预测保证合同的供应以及预测非保证合同的供应。每个机会代表访问网页的用户。每个保证合同保证广告与许多机会的匹配。每个非保证合同保证与广告相关联的用户事件。然后，优化者根据预测的机会供应，预期的保证合同供应，预期的无担保合同供应，以及平衡一组定义代表性的参数的目标函数，生成一个将契约与机会相匹配的计划。合同，与服务非保证合同相关的成本以及与合同相关的业绩目标。

2. 发明申请

US20120005018A1 Large-Scale User Modeling Experiments Using Real-Time Traffic 审中-公开
标题翻译：使用实时流量的大规模用户建模实验
公开(公告)号：US20120005018A1
公开(公告)日：2012-01-05
申请号：US12830259
申请日：2010-07-02
申请人： Vijay Krishna Narayanan , Rajesh Parekh , Albert Meltzer , Sharon Y. Barr , Nilesh Gohel , Utku Irmak , Feng Shao
发明人： Vijay Krishna Narayanan , Rajesh Parekh , Albert Meltzer , Sharon Y. Barr , Nilesh Gohel , Utku Irmak , Feng Shao
IPC分类号： G06Q30/00 , G06F17/30 , G06Q10/00
CPC分类号： G06Q30/02 , G06Q10/067 , G06Q30/0254
摘要： A computer-implemented method for matching a display advertisement to a user within a large-scale, non-destructive user modeling and experimentation environment using real-time traffic. The method commences by populating a user profile object (containing demographics, history, and behaviors of the user) for use during concurrent operation of a production platform and an experimentation platform. To implement non-destructive testing, the method continues by cloning a portion of the real-time traffic for use by the experimentation platform while concurrently delivering the real-time traffic to the production platform. The production platform and the experimentation platform operate concurrently, scoring matches between the user profile objects and a plurality of display advertisements for selecting among the best-scored advertisements. At the conclusion of the experiment, a new user profile object is constructed by selecting a first portion of the experimentation user profile object for use during continued operation of the production platform. Any undesired data is discarded.
摘要翻译：一种用于在使用实时流量的大规模，非破坏性的用户建模和实验环境中将显示广告与用户进行匹配的计算机实现的方法。该方法通过填充用户简档对象（包含用户的人口统计，历史和行为）开始，以在生产平台和实验平台的并发操作期间使用。为了实现非破坏性测试，该方法通过克隆一部分实时流量以供实验平台使用，同时将实时流量同时传递到生产平台。生产平台和实验平台同时运行，在用户简档对象和多个显示广告之间进行匹配，以便在最佳评分的广告之间进行选择。在实验结束时，通过选择实验用户简档对象的第一部分来构建新的用户简档对象，以在生产平台的连续操作期间使用。任何不需要的数据都被丢弃。

3. 发明申请

US20110035273A1 PROFILE RECOMMENDATIONS FOR ADVERTISEMENT CAMPAIGN PERFORMANCE IMPROVEMENT 审中-公开
标题翻译：简介关于广告推广绩效改进的建议
公开(公告)号：US20110035273A1
公开(公告)日：2011-02-10
申请号：US12536334
申请日：2009-08-05
申请人： Jignashu Parikh , Vijay Krishna Narayanan , Rushi P. Bhatt , Xia Wan , Rajesh Parekh
发明人： Jignashu Parikh , Vijay Krishna Narayanan , Rushi P. Bhatt , Xia Wan , Rajesh Parekh
IPC分类号： G06Q30/00 , G06Q10/00
CPC分类号： G06Q30/02 , G06Q30/0243
摘要： A method for recommending improvements to advertisement campaign performance includes receiving a seed campaign insertion order (IO) having one or more campaign IO lines; computing a plurality of neighbor ad campaigns based on comparison of the seed campaign IO with a dataset of advertiser ad campaign IO lines; generating campaign IO recommendations by executing an algorithm to recommend profiles to add to the seed campaign IO from booking lines corresponding to the profiles based on performance of such use by the neighbor ad campaigns being generally above average when compared with campaigns that did not use the recommended profiles; filtering the profile recommendations based on a plurality of performance-enhancing criteria of the seed campaign IO and the neighbor ad campaigns with respect to each potential profile recommendation; ranking the profile recommendations based on at least one performance metric; and displaying the ranked profile recommendations to the advertiser for selection.
摘要翻译：一种用于推荐改进广告活动性能的方法包括：接收具有一个或多个活动IO线的种子活动插入订单（IO）; 基于种子活动IO与广告主广告活动IO行的数据集的比较来计算多个邻居广告活动; 通过执行一种算法，通过执行一种算法来推荐配置文件，以推荐配置文件，以根据与配置文件相对应的预定行添加种子广告系列IO，这些配置文件基于相邻广告系列的使用效果，通常高于平均水平，与未使用推荐的广告系列相比档案; 基于关于每个潜在简档建议的种子活动IO和邻居广告活动的多个绩效增强标准来过滤简档建议; 根据至少一个绩效指标对简档建议进行排名; 并向广告商显示排名的配置文件推荐以进行选择。

4. 发明申请

US20110035272A1 FEATURE-VALUE RECOMMENDATIONS FOR ADVERTISEMENT CAMPAIGN PERFORMANCE IMPROVEMENT 审中-公开
标题翻译：广告推荐性能改进的特色值建议
公开(公告)号：US20110035272A1
公开(公告)日：2011-02-10
申请号：US12536113
申请日：2009-08-05
申请人： Rushi P. Bhatt , Vijay Krishna Narayanan , Rajesh Parekh , Xia Wan
发明人： Rushi P. Bhatt , Vijay Krishna Narayanan , Rajesh Parekh , Xia Wan
IPC分类号： G06Q30/00 , G06Q10/00
CPC分类号： G06Q30/02 , G06Q30/0243 , G06Q30/0244 , G06Q30/0247
摘要： A method for making recommendations to improve advertisement campaign performance includes receiving a seed campaign insertion order (IO) having one or more campaign IO lines; computing a plurality of neighbor ad campaigns based on a comparison of the seed campaign IO with a dataset of advertiser ad campaign IO lines; generating campaign IO recommendations by executing an algorithm to recommend a campaign feature and value (FV) as a change to a line of the seed campaign IO based on success of such use by the neighbor ad campaigns; ranking the FV recommendations based on at least one performance metric; filtering the FV recommendations based on a plurality of performance-enhancing criteria of the seed campaign IO and the neighbor ad campaigns with respect to individual FV recommendations; and displaying the ranked FV recommendations to the advertiser for selection.
摘要翻译：提出改进广告活动性能的方法包括接收具有一个或多个活动IO行的种子活动插入订单（IO）; 基于种子活动IO与广告主广告活动IO行的数据集的比较来计算多个邻居广告活动; 通过执行一种算法，根据邻居广告活动的成功使用推荐广告系列功能和价值（FV）来改变种子广告系列IO的一行，从而产生广告系列IO建议; 根据至少一个绩效指标对FV建议进行排名; 基于关于个人FV建议的种子活动IO和邻居广告活动的多个绩效增强标准来过滤FV建议; 并向广告商显示排名的FV建议以进行选择。

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