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公开(公告)号：US09934514B2
公开(公告)日：2018-04-03
申请号：US14990611
申请日：2016-01-07
Applicant: Facebook, Inc.
Inventor： Cameron Alexander Marlow , Dean Eckles , Brian Karrer , Johan Ugander , Lars Seren Backstrom , Jon Kleinberg
CPC classification number: G06Q30/0244 , G06Q50/01 , H04L67/10 , H04L67/22 , H04L67/306 , H04W4/21
Abstract: In one embodiment, a method includes accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node corresponding to a user of an online social network, identifying a plurality of clusters in the social graph using graph clustering, providing a treatment to a first set of users based on the clusters, and determining a treatment effect treatment for the users in the first set based on a network exposure to the treatment for each user.
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2.发明授权公开(公告)号：US09386080B2
公开(公告)日：2016-07-05
申请号：US14465787
申请日：2014-08-21
Applicant: Facebook, Inc.
Inventor： Michael Nowak , Dean Eckles
CPC classification number: G06F17/3053 , G06F15/16 , G06F17/30554 , G06F17/30684 , G06N99/005 , G06Q10/06 , G06Q30/0251 , G06Q50/01 , H04L51/32 , H04L67/10 , H04L67/306
Abstract: A social networking system obtains linguistic data from a user's text communications on the social networking system. For example, occurrences of words in various types of communications by the user in the social networking system are determined. The linguistic data and non-linguistic data associated with the user are used in a trained model to predict one or more personality characteristics for the user. The inferred personality characteristics are stored in connection with the user's profile, and may be used for targeting, ranking, selecting versions of products, and various other purposes.
Abstract translation: 社交网络系统从社交网络系统的用户文字通信中获取语言数据。 例如，确定用户在社交网络系统中的各种类型的通信中出现的单词。 在训练模型中使用与用户相关联的语言数据和非语言数据来预测用户的一个或多个个性特征。 推测的个性特征与用户的简档相关联地存储，并且可以用于定位，排序，选择产品的版本以及各种其它目的。
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公开(公告)号：US20160117721A1
公开(公告)日：2016-04-28
申请号：US14990611
申请日：2016-01-07
Applicant: Facebook, Inc.
Inventor： Cameron Alexander Marlow , Dean Eckles , Brian Karrer , Johan Ugander , Lars Seren Backstrom , Jon Kleinberg
CPC classification number: G06Q30/0244 , G06Q50/01 , H04L67/10 , H04L67/22 , H04L67/306 , H04W4/21
Abstract: In one embodiment, a method includes accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node corresponding to a user of an online social network, identifying a plurality of clusters in the social graph using graph clustering, providing a treatment to a first set of users based on the clusters, and determining a treatment effect treatment for the users in the first set based on a network exposure to the treatment for each user.
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4.发明申请公开(公告)号：US20140365577A1
公开(公告)日：2014-12-11
申请号：US14465787
申请日：2014-08-21
Applicant: Facebook, Inc.
Inventor： Michael Nowak , Dean Eckles
IPC: H04L29/08
CPC classification number: G06F17/3053 , G06F15/16 , G06F17/30554 , G06F17/30684 , G06N99/005 , G06Q10/06 , G06Q30/0251 , G06Q50/01 , H04L51/32 , H04L67/10 , H04L67/306
Abstract: A social networking system obtains linguistic data from a user's text communications on the social networking system. For example, occurrences of words in various types of communications by the user in the social networking system are determined. The linguistic data and non-linguistic data associated with the user are used in a trained model to predict one or more personality characteristics for the user. The inferred personality characteristics are stored in connection with the user's profile, and may be used for targeting, ranking, selecting versions of products, and various other purposes.
Abstract translation: 社交网络系统从社交网络系统的用户文字通信中获取语言数据。 例如，确定用户在社交网络系统中的各种类型的通信中出现的单词。 在训练模型中使用与用户相关联的语言数据和非语言数据来预测用户的一个或多个个性特征。 推测的个性特征与用户的简档相关联地存储，并且可以用于定位，排序，选择产品的版本以及各种其它目的。
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Patent Agency Ranking
公开(公告)号：US10528973B2
公开(公告)日：2020-01-07
申请号：US15887628
申请日：2018-02-02
Applicant: Facebook, Inc.
Inventor： Cameron Alexander Marlow , Dean Eckles , Brian Karrer , Johan Ugander , Lars Seren Backstrom , Jon Kleinberg
Abstract: In one embodiment, a method includes sending, from an application server to a first set of client systems, instructions for providing a treatment to a first set of users. The method includes determining an average treatment effect of the treatment for the first set of users based on information about user interactions associated with the treatment and a network exposure to the treatment for each user. Network exposure for a user is a measure of other users associated with the user that have been provided the treatment. The method includes modifying the treatment based on the determined average treatment effect. The method includes sending, to a second set of client systems, instructions for providing the modified treatment to a second set of users. The second set of users is a discrete, non-overlapping set of users with respect to the first set.
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公开(公告)号：US09740752B2
公开(公告)日：2017-08-22
申请号：US15173009
申请日：2016-06-03
Applicant: Facebook, Inc.
Inventor： Michael Nowak , Dean Eckles
CPC classification number: G06F17/3053 , G06F15/16 , G06F17/30554 , G06F17/30684 , G06N99/005 , G06Q10/06 , G06Q30/0251 , G06Q50/01 , H04L51/32 , H04L67/10 , H04L67/306
Abstract: A social networking system obtains linguistic data from a user's text communications on the social networking system. For example, occurrences of words in various types of communications by the user in the social networking system are determined. The linguistic data and non-linguistic data associated with the user are used in a trained model to predict one or more personality characteristics for the user. The inferred personality characteristics are stored in connection with the user's profile, and may be used for targeting, ranking, selecting versions of products, and various other purposes.
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7.发明申请公开(公告)号：US20160283485A1
公开(公告)日：2016-09-29
申请号：US15173009
申请日：2016-06-03
Applicant: Facebook, Inc.
Inventor： Michael Nowak , Dean Eckles
CPC classification number: G06F17/3053 , G06F15/16 , G06F17/30554 , G06F17/30684 , G06N99/005 , G06Q10/06 , G06Q30/0251 , G06Q50/01 , H04L51/32 , H04L67/10 , H04L67/306
Abstract: A social networking system obtains linguistic data from a user's text communications on the social networking system. For example, occurrences of words in various types of communications by the user in the social networking system are determined. The linguistic data and non-linguistic data associated with the user are used in a trained model to predict one or more personality characteristics for the user. The inferred personality characteristics are stored in connection with the user's profile, and may be used for targeting, ranking, selecting versions of products, and various other purposes.
Abstract translation: 社交网络系统从社交网络系统的用户文字通信中获取语言数据。 例如，确定用户在社交网络系统中的各种类型的通信中出现的单词。 在训练模型中使用与用户相关联的语言数据和非语言数据来预测用户的一个或多个个性特征。 推测的个性特征与用户的简档相关联地存储，并且可以用于定位，排序，选择产品的版本以及各种其它目的。
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公开(公告)号：US09292884B2
公开(公告)日：2016-03-22
申请号：US13939093
申请日：2013-07-10
Applicant: Facebook, Inc.
Inventor： Cameron Alexander Marlow , Dean Eckles , Brian Karrer , Johan Ugander , Lars Seren Backstrom , Jon Kleinberg
CPC classification number: G06Q30/0244 , G06Q50/01 , H04L67/10 , H04L67/22 , H04L67/306 , H04W4/21
Abstract: In one embodiment, a method includes accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node corresponding to a user of an online social network, identifying a plurality of clusters in the social graph using graph clustering, providing a treatment to a first set of users based on the clusters, and determining a treatment effect treatment for the users in the first set based on a network exposure to the treatment for each user.
Abstract translation: 在一个实施例中，一种方法包括访问包括多个节点和连接节点的多个边缘的社交图，每个节点对应于在线社交网络的用户，使用图形聚类识别社交图中的多个聚类， 基于群集向第一组用户提供治疗，并且基于针对每个用户的治疗的网络暴露来确定第一组中的用户的治疗效果治疗。
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公开(公告)号：US20150019639A1
公开(公告)日：2015-01-15
申请号：US13939093
申请日：2013-07-10
Applicant: Facebook, Inc.
Inventor： Cameron Alexander Marlow , Dean Eckles , Brian Karrer , Johan Ugander , Lars Seren Backstrom , Jon Kleinberg
IPC: H04L29/06
CPC classification number: G06Q30/0244 , G06Q50/01 , H04L67/10 , H04L67/22 , H04L67/306 , H04W4/21
Abstract: In one embodiment, a method includes accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node corresponding to a user of an online social network, identifying a plurality of clusters in the social graph using graph clustering, providing a treatment to a first set of users based on the clusters, and determining a treatment effect treatment for the users in the first set based on a network exposure to the treatment for each user.
Abstract translation: 在一个实施例中，一种方法包括访问包括多个节点和连接节点的多个边缘的社交图，每个节点对应于在线社交网络的用户，使用图形聚类识别社交图中的多个聚类， 基于群集向第一组用户提供治疗，并且基于针对每个用户的治疗的网络暴露来确定第一组中的用户的治疗效果治疗。
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