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    ONLINE AD CAMPAIGN TUNING WITH PID CONTROLLERS
    1.
    发明申请
    ONLINE AD CAMPAIGN TUNING WITH PID CONTROLLERS 审中-公开
    带PID控制器的在线广告调试

    公开(公告)号：US20160110755A1

    公开(公告)日：2016-04-21

    申请号：US14518601

    申请日：2014-10-20

    Applicant: Yahoo! Inc.

    Inventor： Yury Smirnov ,  Quan Lu ,  Kuang-chih Lee

    IPC: G06Q30/02

    CPC classification number: G06Q30/0244

    Abstract: Described herein are techniques and systems for online ad campaign tuning using proportional-integral-derivative (PID) controllers, such as proportional (P) controllers and proportional-integral (PI) controllers. Also, described herein are techniques and systems for shortening a learning/tuning phase of a PID controller used for optimizing an online ad campaign.

    Abstract translation: 这里描述了使用比例积分微分（PID）控制器（例如比例（P）控制器和比例积分（PI））控制器在线广告活动调整的技术和系统。 此外，这里描述的是用于缩短用于优化在线广告活动的PID控制器的学习/调整阶段的技术和系统。

    EXPLORATION OF REAL-TIME ADVERTISING DECISIONS
    3.
    发明申请
    EXPLORATION OF REAL-TIME ADVERTISING DECISIONS 审中-公开

    公开(公告)号：US20170098236A1

    公开(公告)日：2017-04-06

    申请号：US14873757

    申请日：2015-10-02

    Applicant: Yahoo! Inc.

    Inventor： Kuang-chih Lee ,  Quan Lu ,  Giovanni Gardelli ,  Donglin Niu

    IPC: G06Q30/02 ,  G06F17/30 ,  G06Q10/06

    CPC classification number: G06Q30/0244 ,  G06Q10/067 ,  G06Q30/0247 ,  G06Q30/0275

    Abstract: Described herein are example systems and operations for enhancing response prediction and bidding decision making. A feature recommendation controller may include a factorization machine that generates a set of combinations of contextual and advertiser features yielding high expected response rates. A bidding controller may implement a multi-arm bandit system that uses Thompson sampling to select an optimal one of the feature combinations that corresponds to a highest expected response rate. The bidding controller may compare the corresponding highest expected response rate with a threshold response rate associated with a pacing rate to determine whether to place a bid for a received ad request.

    SYSTEM AND METHOD FOR CONTEXTUAL VIDEO ADVERTISEMENT SERVING IN GUARANTEED DISPLAY ADVERTISING
    5.
    发明申请
    SYSTEM AND METHOD FOR CONTEXTUAL VIDEO ADVERTISEMENT SERVING IN GUARANTEED DISPLAY ADVERTISING 审中-公开
    用于保证展示广告服务的上下文视频广告系统和方法

    公开(公告)号：US20170032424A1

    公开(公告)日：2017-02-02

    申请号：US14815334

    申请日：2015-07-31

    Applicant: Yahoo! Inc.

    Inventor： Suleyman Cetintas ,  Srinath Ravindran ,  Mohammad Saberian ,  Sandeep Soni ,  Kuang-chih Lee ,  Hong Yao ,  Jian Yang ,  Pradhan Pattanayak

    IPC: G06Q30/02

    CPC classification number: G06Q30/0269 ,  G06Q30/0277

    Abstract: The technologies described herein serve contextually relevant advertisements under a guaranteed advertisement campaign. A publisher retrieves a guaranteed advertisement campaign related to a webpage available for serving an advertisement, and identifies a set of advertisements relating to the guaranteed advertisement campaign. Advertisement selecting circuitry of the publisher determines whether an advertisement that is contextually relevant to content published at the webpage is present in the set of advertisements. If there is no contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects an alternative advertisement from the set of advertisements that minimizes an under-delivery risk related to the guaranteed advertisement campaign. If there is a contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects the contextually relevant advertisement. Then, the publisher provides the selected advertisement to a client device.

    Abstract translation: 本文描述的技术在保证的广告活动下提供与内容相关的广告。 发布者检索与可用于服务广告的网页有关的保证广告活动，并且识别与保证广告活动相关的一组广告。 发布者的广告选择电路决定在该广告集中是否存在与在网页上发布的内容上下文相关的广告。 如果广告集合中没有上下文相关的广告，则广告选择电路从该广告集合中选择一个替代的广告，使与保证的广告活动相关的不足的风险最小化。 如果广告集合中存在上下文相关的广告，则广告选择电路选择上下文相关的广告。 然后，发布者将所选择的广告提供给客户端设备。

    INDUCTIVE MATRIX COMPLETION AND GRAPH PROXIMITY FOR CONTENT ITEM RECOMMENDATION
    6.
    发明申请
    INDUCTIVE MATRIX COMPLETION AND GRAPH PROXIMITY FOR CONTENT ITEM RECOMMENDATION 审中-公开
    感应矩阵完成和内容项目推荐的图像近似

    公开(公告)号：US20160299992A1

    公开(公告)日：2016-10-13

    申请号：US14682603

    申请日：2015-04-09

    Applicant: Yahoo!, Inc.

    Inventor： Suleyman Cetintas ,  Kuang-chih Lee

    IPC: G06F17/30

    CPC classification number: G06F16/951 ,  G06F16/3331

    Abstract: Users may consume and/or share information through various types of content items. For example, user may post a family photo through a social network, create a running blog through a microblogging service, etc. Because users may be overwhelmed by the amount of available content items, it may be advantageous to recommend content items, such as blogs to follow, to users. Accordingly, inductive matrix completion is used to evaluate user interactions with content items (e.g., a user following a blog), content item features (e.g., text and/or images of a blog is evaluated to identify a topic of the blog), and/or user features (e.g., a user liking or reblogging a blog, user demographics, user interests, etc.) to determine whether to recommend a content item to a user. Additionally, graph proximity is used to recommend content items based upon weights of edges connecting user nodes to content item nodes within a directed graph.

    Abstract translation: 用户可以通过各种内容项目消费和/或共享信息。 例如，用户可以通过社交网络发布家庭照片，通过微博服务创建一个正在运行的博客等等。由于用户可能被可用内容项目的数量所压倒，因此推荐内容项目（如博客）可能是有利的 跟随，给用户。 因此，使用感性矩阵完成来评估用户与内容项目的交互（例如，跟随博客的用户），内容项目特征（例如，评估博客的文本和/或图像以识别博客的主题），以及 /或用户特征（例如，用户喜好或重新登录博客，用户人口统计，用户兴趣等）来确定是否向用户推荐内容项。 另外，图形邻近度用于基于将用户节点连接到有向图中的内容项目节点的边缘的权重来推荐内容项目。

    PACING CONTROL FOR ONLINE AD CAMPAIGNS
    7.
    发明申请
    PACING CONTROL FOR ONLINE AD CAMPAIGNS 审中-公开
    在线广告的控制

    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。

    GENERATING PREFERENCE INDICES FOR IMAGE CONTENT
    8.
    发明申请
    GENERATING PREFERENCE INDICES FOR IMAGE CONTENT 有权
    生成图像内容的偏好指标

    公开(公告)号：US20160180162A1

    公开(公告)日：2016-06-23

    申请号：US14579998

    申请日：2014-12-22

    Applicant: Yahoo! Inc.

    Inventor： Suleyman Cetintas ,  Kuang-chih Lee ,  Jia Li

    IPC: G06K9/00 ,  G06K9/62 ,  G06F3/0484 ,  G06N3/08 ,  G06F17/30

    CPC classification number: G06K9/6267 ,  G06F3/04842 ,  G06F17/30265 ,  G06K9/00456 ,  G06K9/00664 ,  G06K9/4628 ,  G06K9/6201 ,  G06K9/626 ,  G06K9/627 ,  G06N3/08

    Abstract: Briefly, embodiments of methods and/or systems of generating preference indices for contiguous portions of digital images are disclosed. For one embodiment, as an example, parameters of a neural network may be developed to generate object labels for digital images. The developed parameters may be transferred to a neural network utilized to generate signal sample value levels corresponding to preference indices for contiguous portions of digital images.

    Abstract translation: 简而言之，公开了为数字图像的连续部分生成偏好索引的方法和/或系统的实施例。 对于一个实施例，作为示例，可以开发神经网络的参数以生成数字图像的对象标签。 所开发的参数可以被传送到用于产生对应于数字图像的连续部分的偏好索引的信号样本值级别的神经网络。

    SYSTEMS AND METHODS FOR ONLINE ADVERTISEMENT REALIZATION PREDICTION
    9.
    发明申请
    SYSTEMS AND METHODS FOR ONLINE ADVERTISEMENT REALIZATION PREDICTION 审中-公开
    在线广告实现预测的系统和方法

    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

    IPC: G06Q30/02 ,  G06N5/04 ,  G06N7/00

    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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