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公开(公告)号：US20170068992A1
公开(公告)日：2017-03-09
申请号：US14846618
申请日：2015-09-04
Applicant: Yahoo! Inc.
Inventor： Kehan Chen , Jian Xu , Yu Zou
CPC classification number: G06Q30/0269 , H04L65/4069 , H04L67/22
Abstract: A method and apparatus for multi-source content blending.
Abstract translation: 一种用于多源内容混合的方法和装置。
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公开(公告)号：US20160189207A1
公开(公告)日：2016-06-30
申请号：US14740937
申请日：2015-06-16
Applicant: Yahoo! Inc.
Inventor： Jian Xu , Xuhui Shao , Jianjie Ma , Quan Lu
IPC: G06Q30/02
CPC classification number: G06Q30/0249 , G06Q30/0264 , G06Q30/0269 , G06Q30/0275 , G06Q30/0277
Abstract: Described herein are example systems and operations for enhancing targeted delivery of online content using action rate lift and/or A/B testing. These examples provide solutions to problems in targeted delivery of online content, such as the problem of not being able to identify audience and/or situational targets mostly or only influenced by the content item or campaign of concern. For example, described herein are solutions that can estimate AR lift associated with a content item, and then distribute the content item or similar content items accordingly. An AR lift model can be used and such a model can use machine learning, A/B testing, and/or statistical analysis.
Abstract translation: 这里描述的是使用动作速率提升和/或A / B测试来增强在线内容的目标传送的示例系统和操作。 这些例子为有针对性地提供在线内容的问题提供了解决方案，例如无法识别受众和/或情境目标的问题，主要或仅受内容项目或关注活动的影响。 例如，这里描述的是可以估计与内容项目相关联的AR提升，然后相应地分发内容项目或类似内容项目的解决方案。 可以使用AR提升模型，这种模型可以使用机器学习，A / B测试和/或统计分析。
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公开(公告)号：US20160180376A1
公开(公告)日：2016-06-23
申请号：US14585961
申请日：2014-12-30
Applicant: Yahoo! Inc.
Inventor： Zhonghao LU , Jian Xu , Lixing Bo
IPC: G06Q30/02
CPC classification number: G06Q30/0244
Abstract: A computer system that implements a method for optimizing an ad campaign may be configured to receive an online ad display request to display an ad to a viewer and obtain at least three probabilities—a first probability that the ad will receive a positive response from the viewer, a second probability that the ad will receive a neutral response from the viewer, and a third probability that the ad will receive a negative response from the viewer. Additionally, the computer system may also be configured to determine a gain value of displaying the ad; and determine a bidding price associated with the ad request based on the gain value.
Abstract translation: 实现用于优化广告活动的方法的计算机系统可以被配置为接收在线广告显示请求以向观看者显示广告并获得至少三个概率 - 广告将从观看者接收到肯定响应的第一概率 ，广告将从观众接收中立响应的第二个概率，以及广告将从观众收到否定回应的第三个概率。 此外，计算机系统还可以被配置为确定显示广告的增益值; 并基于增益值确定与广告请求相关联的投标价格。
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Patent Agency Ranking
公开(公告)号：US20160180372A1
公开(公告)日：2016-06-23
申请号：US14577223
申请日：2014-12-19
Applicant: Yahoo! Inc.
Inventor： Quan LU , Kuang-chih Lee , Donglin Niu , Jian Xu
CPC classification number: G06Q30/0242
Abstract: A computer system implementing a method for ad realization prediction may be configured to receive a plurality of target realization factors associated with a target ad display opportunity; determine a reference realization probability score of the target ad display opportunity based on a global reference realization probability distribution associated with an ad display realization probability decision tree; using the reference realization probability score, determine an ad realization probability score of the target ad display opportunity according to a piecewise calibrated realization probability function; and return the ad realization probability score.
Abstract translation: 实现用于广告实现预测的方法的计算机系统可以被配置为接收与目标广告显示机会相关联的多个目标实现因素; 基于与广告显示实现概率决策树相关联的全局参考实现概率分布来确定目标广告显示机会的参考实现概率得分; 使用参考实现概率分数，根据分段校准的实现概率函数确定目标广告显示机会的广告实现概率分数; 并返回广告实现概率得分。
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公开(公告)号：US20160092933A1
公开(公告)日：2016-03-31
申请号：US14497546
申请日：2014-09-26
Applicant: Yahoo!, Inc.
Inventor： Jian Xu , Chunming Wang , Ming Chang
IPC: G06Q30/02
CPC classification number: G06Q30/0275
Abstract: A demand-side platform (DSP) may bid on advertising opportunities (e.g., provided by a supply-side platform (SSP)) on behalf of an advertiser wishing to place an advertisement, such as part of an advertisement campaign. A target advertisement may be selected based upon various criteria, and a bid for the target advertisement to run during the advertising opportunity is made in a manner that satisfies one or more goals of the advertisement campaign while also being beneficial to the DSP. For example, the target advertisement may be selected from a reduced problem space where merely advertisements corresponding to a target advertising opportunity class are evaluated, where the target opportunity class corresponds to an opportunity class of the advertising opportunity. Win rate modeling data, inventory cost modeling data, user response modeling data, and/or other information may be used to select the target advertisement.
Abstract translation: 需求侧平台（DSP）可以代表希望放置广告的广告商（例如广告活动的一部分）来竞标广告机会（例如由供应方平台（SSP）提供）。 可以基于各种标准来选择目标广告，并且以满足广告活动的一个或多个目标的方式进行在广告机会期间运行的目标广告的出价，同时也有利于DSP。 例如，可以从减少的问题空间中选择目标广告，其中仅评估与目标广告机会类对应的广告，其中目标机会类对应于广告机会的机会类。 赢利率建模数据，库存成本建模数据，用户响应建模数据和/或其他信息可用于选择目标广告。
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公开(公告)号：US20160188725A1
公开(公告)日：2016-06-30
申请号：US14586202
申请日：2014-12-30
Applicant: Yahoo! Inc.
Inventor： Chunming Wang , Jian Xu , Liang Wang , Yu Zou , Hao Zheng
IPC: G06F17/30
Abstract: Method, system, and programs for providing content recommendation are disclosed. A first set of candidate content items may be generated based on a user profile, and a second set of candidate items may be generated based on the likelihood that the user will click a corresponding candidate content item in the second set. The candidate content items in the first and second sets may be ranked together using a learning model and presented to the user as content recommendations based on their rankings. The likelihood that the user will click a given candidate content item in the second set may be estimated based on similarities between the given content item and content items related to the given content item. Such a similarity may be computed based on activities performed by users who have viewed both the given content item and a related content item.
Abstract translation: 公开了用于提供内容推荐的方法，系统和程序。 可以基于用户简档来生成第一组候选内容项，并且可以基于用户将点击第二组中的相应候选内容项的可能性来生成第二组候选项。 可以使用学习模型将第一和第二组中的候选内容项目排列在一起，并且基于其排名将其呈现给用户作为内容推荐。 可以基于给定内容项和与给定内容项相关的内容项之间的相似度来估计用户点击第二组中的给定候选内容项的可能性。 可以基于同时观看给定内容项目和相关内容项目的用户执行的活动来计算这样的相似度。
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公开(公告)号：US20160180373A1
公开(公告)日：2016-06-23
申请号：US14573979
申请日：2014-12-17
Applicant: Yahoo! Inc.
Inventor： Jian Xu , Kuang-chih Lee , Wentong Li , Hang Qi , Quan Lu
IPC: G06Q30/02
CPC classification number: G06Q30/0244 , G06Q30/0272
Abstract: Described herein are techniques and systems for online ad campaign pacing. The techniques described herein use budget allocation along with the estimations of bids and response rates. With use of budget allocation, the techniques can use budget pacing to enhance impressions and maximize desired responses, such as desired click-through rates. These techniques focus on enhancing pacing and performance of ad campaigns, such as enhancing performance across distinct and/or unified online ad marketplaces. These techniques are especially useful in the context of a demand-side platform (DSP). In some examples, the techniques assume that impression supply is much larger than advertiser demand for impressions of their ads, so such techniques focus on selecting high performing inventory of ad space. Yet, with such a focus, a smooth or consistent delivery of ads over time is used.
Abstract translation: 这里描述了在线广告系列投放安排的技术和系统。 本文描述的技术使用预算分配以及出价和响应率的估计。 通过使用预算分配，这些技术可以使用预算投放安排来增加展示次数并最大化期望的响应，例如所需的点击率。 这些技术专注于提高广告系列的投放安排和效果，例如提升不同的和/或统一的在线广告市场的效能。 这些技术在需求侧平台（DSP）的上下文中特别有用。 在一些示例中，这些技术假定，对于广告的展示次数，展示供应量远远大于广告客户的需求，因此此类技术将重点放在选择高性能的广告空间广告资源。 然而，随着时间的推移，广告的流畅或一致性得到了这样的关注。
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公开(公告)号：US09886705B2
公开(公告)日：2018-02-06
申请号：US14497546
申请日：2014-09-26
Applicant: Yahoo!, Inc.
Inventor： Jian Xu , Chunming Wang , Ming Chang
CPC classification number: G06Q30/0275
Abstract: A demand-side platform (DSP) may bid on advertising opportunities (e.g., provided by a supply-side platform (SSP)) on behalf of an advertiser wishing to place an advertisement, such as part of an advertisement campaign. A target advertisement may be selected based upon various criteria, and a bid for the target advertisement to run during the advertising opportunity is made in a manner that satisfies one or more goals of the advertisement campaign while also being beneficial to the DSP. For example, the target advertisement may be selected from a reduced problem space where merely advertisements corresponding to a target advertising opportunity class are evaluated, where the target opportunity class corresponds to an opportunity class of the advertising opportunity. Win rate modeling data, inventory cost modeling data, user response modeling data, and/or other information may be used to select the target advertisement.
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