Targeting stories based on influencer scores

    公开(公告)号:US10163136B2

    公开(公告)日:2018-12-25

    申请号:US15402155

    申请日:2017-01-09

    Applicant: Facebook, Inc.

    Abstract: A story describing an activity performed by an interacting user is distributed to viewing users according to the influencer scores for the viewing users. Each influencer score can be calculated based at least in part on the influence of a viewing user on those users connected to the viewing user, and on the influencer scores for the users connected to the viewing user. Based on the determined influencer scores, at least one of the viewing users can be provided with the story describing the activity performed by the interacting user.

    Targeting stories based on influencer scores
    3.
    发明授权
    Targeting stories based on influencer scores 有权
    以影响分数为目标的故事

    公开(公告)号:US09576016B2

    公开(公告)日:2017-02-21

    申请号:US14981361

    申请日:2015-12-28

    Applicant: Facebook, Inc.

    Abstract: A story describing an activity performed by an interacting user is distributed to viewing users according to the influencer scores for the viewing users. Each influencer score can be calculated based at least in part on the influence of a viewing user on those users connected to the viewing user, and on the influencer scores for the users connected to the viewing user. Based on the determined influencer scores, at least one of the viewing users can be provided with the story describing the activity performed by the interacting user.

    Abstract translation: 描述由交互用户执行的活动的故事根据观看用户的影响者分数分发给观看用户。 可以至少部分地基于观看用户对连接到观看用户的用户的影响以及连接到观看用户的用户的影响者得分来计算每个影响者得分。 基于所确定的影响者评分,可以向观看用户中的至少一个提供描述由交互用户执行的活动的故事。

    Using Polling Results as Discrete Metrics For Content Quality Prediction Model
    4.
    发明申请
    Using Polling Results as Discrete Metrics For Content Quality Prediction Model 审中-公开
    使用轮询结果作为内容质量预测模型的离散度量

    公开(公告)号:US20140229234A1

    公开(公告)日:2014-08-14

    申请号:US14253138

    申请日:2014-04-15

    Applicant: Facebook, Inc.

    CPC classification number: G06Q30/0245 G06N5/048 G06Q30/02 G06Q30/0202

    Abstract: A social networking system presents content items to users, who then provide feedback regarding pairs of content items. The feedback includes a selection of a content item of the pair of content items that was preferred by the user over the other content item. The social networking system uses this information to train a predictive model that scores content items based on quality. The content items may be advertisements. The social networking system uses the pair-wise comparisons of the advertisements to determine feedback coefficients in an advertising quality score prediction model using regression analysis of the pair-wise comparisons for each predictive factor in the model. In this way, the pair-wise comparisons are used to train the prediction model to understand which advertisements are more enjoyable than others. A feedback coefficient for each predictive factor may be computed based on the preferences received from the group of users.

    Abstract translation: 社交网络系统向用户呈现内容,然后他们提供关于内容对的反馈。 反馈包括用户对其他内容项目优选的内容项目对的内容项的选择。 社交网络系统使用该信息来训练基于质量对内容项进行评分的预测模型。 内容项可以是广告。 社交网络系统使用广告的成对比较来确定广告质量得分预测模型中的反馈系数,其使用对于模型中的每个预测因子的成对比较的回归分析。 以这种方式,使用成对比较来训练预测模型,以了解哪些广告比其他广告更愉快。 可以基于从用户组接收的偏好来计算每个预测因子的反馈系数。

    SELECTING SOCIAL CONTEXT FOR SPONSORED STORIES IN A SOCIAL NETWORKING SYSTEM
    5.
    发明申请
    SELECTING SOCIAL CONTEXT FOR SPONSORED STORIES IN A SOCIAL NETWORKING SYSTEM 审中-公开
    选择在社会网络系统中赞助的故事的社会背景

    公开(公告)号:US20140222802A1

    公开(公告)日:2014-08-07

    申请号:US13759838

    申请日:2013-02-05

    Applicant: Facebook, Inc.

    CPC classification number: G06F16/248 G06Q30/0241 G06Q50/01

    Abstract: A viewing user is provided with sponsored stories describes actions of a user connected to the viewing user associated with an object promoted by an advertiser or actions otherwise promoted by the advertiser. Based on a performance metric, the social networking system selects the user or action to be described by the sponsored story. For example, the social networking system ranks candidate sponsored stories describing different actions or users and selects a candidate sponsored story to increase the likelihood of a viewing user interacting with the selected candidate sponsored story.

    Abstract translation: 查看用户被提供有赞助的故事,描述了连接到与广告主提出的对象相关联的观看用户的用户的动作或由广告主另外宣传的动作。 基于性能指标,社交网络系统选择由赞助故事描述的用户或动作。 例如,社交网络系统将候选赞助的故事描述为描述不同的动作或用户,并选择候选赞助的故事,以增加观看用户与所选择的候选赞助故事交互的可能性。

    BIASING SELECTION OF ADVERTISING BASED ON REAL-TIME USER INTERACTIONS IN A SOCIAL NETWORKING SYSTEM
    6.
    发明申请
    BIASING SELECTION OF ADVERTISING BASED ON REAL-TIME USER INTERACTIONS IN A SOCIAL NETWORKING SYSTEM 审中-公开
    基于社交网络系统中实时用户交互的偏好选择广告

    公开(公告)号:US20140207568A1

    公开(公告)日:2014-07-24

    申请号:US13749358

    申请日:2013-01-24

    Applicant: Facebook, Inc.

    CPC classification number: G06Q30/0251 G06Q50/01

    Abstract: A social networking system receives advertisement requests from advertisers describing information about advertisements and determines one or more ad topics associated with the advertisements. When an advertisement is to be presented to a user, the social networking system determines one or more topics associated with the user from actions performed by the user and identifies candidate advertisements having ad topics matching, or similar to, the topics associated with the user. The topics associated with the user may be determined based on the user's most recent actions. One or more of the candidate advertisements are selected for presentation to the user.

    Abstract translation: 社交网络系统从广告商接收描述关于广告的信息的广告请求,并且确定与广告相关联的一个或多个广告主题。 当要向用户呈现广告时,社交网络系统从用户执行的动作确定与用户相关联的一个或多个主题,并且识别具有与用户相关联的主题匹配或类似的广告主题的候选广告。 可以基于用户的最近的动作来确定与用户相关联的主题。 选择候选广告中的一个或多个以呈现给用户。

    INFERRING TARGET CLUSTERS BASED ON SOCIAL CONNECTIONS
    7.
    发明申请
    INFERRING TARGET CLUSTERS BASED ON SOCIAL CONNECTIONS 有权
    基于社会关系的传播目标群

    公开(公告)号:US20140089400A1

    公开(公告)日:2014-03-27

    申请号:US13625633

    申请日:2012-09-24

    Applicant: FACEBOOK, INC.

    Abstract: A seed cluster comprising a group of users who share a particular attribute and/or affiliation is determined by a social networking system. For each user of the seed cluster, other users and/or entities connected to the user in the social networking system are retrieved. For each retrieved other user or entity, the social networking system may determine whether the other user or entity exhibits the attribute or affiliation based on a random walk algorithm. A resulting targeting cluster of users and/or entities may be used for targeting advertisements targeting to members. A social networking system may also infer an affiliation for a user based on the user's interaction with a page, application, or entity where other users who interacted with the same page, application, or entity have the same affiliation.

    Abstract translation: 包括共享特定属性和/或隶属的一组用户的种子群由社交网络系统确定。 对于种子群的每个用户,检索在社交网络系统中连接到用户的其他用户和/或实体。 对于每个检索到的其他用户或实体,社交网络系统可以基于随机游走算法确定其他用户或实体是否展现属性或隶属关系。 用户和/或实体的结果定向集群可以用于定向到成员的广告。 社交网络系统还可以基于用户与页面,应用程序或实体的交互来推断用户的联系,其中与同一页面,应用程序或实体交互的其他用户具有相同的隶属关系。

    Using polling results as discrete metrics for content quality prediction model
    8.
    发明授权
    Using polling results as discrete metrics for content quality prediction model 有权
    使用轮询结果作为内容质量预测模型的离散度量

    公开(公告)号:US09582812B2

    公开(公告)日:2017-02-28

    申请号:US14253138

    申请日:2014-04-15

    Applicant: Facebook, Inc.

    CPC classification number: G06Q30/0245 G06N5/048 G06Q30/02 G06Q30/0202

    Abstract: A social networking system presents content items to users, who then provide feedback regarding pairs of content items. The feedback includes a selection of a content item of the pair of content items that was preferred by the user over the other content item. The social networking system uses this information to train a predictive model that scores content items based on quality. The content items may be advertisements. The social networking system uses the pair-wise comparisons of the advertisements to determine feedback coefficients in an advertising quality score prediction model using regression analysis of the pair-wise comparisons for each predictive factor in the model. In this way, the pair-wise comparisons are used to train the prediction model to understand which advertisements are more enjoyable than others. A feedback coefficient for each predictive factor may be computed based on the preferences received from the group of users.

    Abstract translation: 社交网络系统向用户呈现内容,然后他们提供关于内容对的反馈。 反馈包括用户对其他内容项目优选的内容项目对的内容项的选择。 社交网络系统使用该信息来训练基于质量对内容项进行评分的预测模型。 内容项可以是广告。 社交网络系统使用广告的成对比较来确定广告质量得分预测模型中的反馈系数,其使用对于模型中的每个预测因子的成对比较的回归分析。 以这种方式,使用成对比较来训练预测模型,以了解哪些广告比其他广告更愉快。 可以基于从用户组接收的偏好来计算每个预测因子的反馈系数。

    INFERRING TARGET CLUSTERS BASED ON SOCIAL CONNECTIONS

    公开(公告)号:US20160267550A1

    公开(公告)日:2016-09-15

    申请号:US15161083

    申请日:2016-05-20

    Applicant: Facebook, Inc.

    Abstract: A seed cluster comprising a group of users who share a particular attribute and/or affiliation is determined by a social networking system. For each user of the seed cluster, other users and/or entities connected to the user in the social networking system are retrieved. For each retrieved other user or entity, the social networking system may determine whether the other user or entity exhibits the attribute or affiliation based on a random walk algorithm. A resulting targeting cluster of users and/or entities may be used for targeting advertisements targeting to members. A social networking system may also infer an affiliation for a user based on the user's interaction with a page, application, or entity where other users who interacted with the same page, application, or entity have the same affiliation.

    INFERRING TARGET CLUSTERS BASED ON SOCIAL CONNECTIONS
    10.
    发明申请
    INFERRING TARGET CLUSTERS BASED ON SOCIAL CONNECTIONS 审中-公开
    基于社会关系的传播目标群

    公开(公告)号:US20160267549A1

    公开(公告)日:2016-09-15

    申请号:US15161079

    申请日:2016-05-20

    Applicant: Facebook, Inc.

    Abstract: A seed cluster comprising a group of users who share a particular attribute and/or affiliation is determined by a social networking system. For each user of the seed cluster, other users and/or entities connected to the user in the social networking system are retrieved. For each retrieved other user or entity, the social networking system may determine whether the other user or entity exhibits the attribute or affiliation based on a random walk algorithm. A resulting targeting cluster of users and/or entities may be used for targeting advertisements targeting to members. A social networking system may also infer an affiliation for a user based on the user's interaction with a page, application, or entity where other users who interacted with the same page, application, or entity have the same affiliation.

    Abstract translation: 包括共享特定属性和/或隶属的一组用户的种子群由社交网络系统确定。 对于种子群的每个用户,检索在社交网络系统中连接到用户的其他用户和/或实体。 对于每个检索到的其他用户或实体,社交网络系统可以基于随机游走算法确定其他用户或实体是否展现属性或隶属关系。 用户和/或实体的结果定向集群可以用于定向到成员的广告。 社交网络系统还可以基于用户与页面,应用程序或实体的交互来推断用户的联系,其中与同一页面,应用程序或实体交互的其他用户具有相同的隶属关系。

Patent Agency Ranking