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    Semi-supervised learning via deep label propagation
    1.
    发明授权
    Semi-supervised learning via deep label propagation 有权

    公开(公告)号：US10922609B2

    公开(公告)日：2021-02-16

    申请号：US15597290

    申请日：2017-05-17

    Applicant: Facebook, Inc.

    Inventor： Aditya Pal ,  Deepayan Chakrabarti ,  Karthik Subbian ,  Anitha Kannan

    IPC: G06N3/08 ,  G06F16/901 ,  G06N3/04 ,  G06N5/02 ,  G06N20/10

    Abstract: In one embodiment, a system may access a graph data structure that includes nodes and connections between the nodes. Each node may be associated with a user; each connection between two nodes may represent a relationship between the associated users; and each node may be either labeled or unlabeled with respect to a label type. For each labeled node, a label of the label type of that labeled node may be propagated to other nodes through the connections. For each node, the system may store a label distribution information associated with the label type based on the propagated labels reaching the node. The system may train a machine-learning model using the labels and the label distribution information of a set of the labeled nodes. A predicted label for each unlabeled node may be generated using the model and the label distribution information of the unlabeled node.

    LABEL INFERENCE IN A SOCIAL NETWORK
    2.
    发明申请
    LABEL INFERENCE IN A SOCIAL NETWORK 审中-公开

    公开(公告)号：US20170124467A1

    公开(公告)日：2017-05-04

    申请号：US15375050

    申请日：2016-12-09

    Applicant: Facebook, Inc.

    Inventor： Deepayan Chakrabarti ,  Sofus Attila Macskassy ,  Stanislav Funiak ,  Jonathan Chang

    IPC: G06N5/04 ,  G06Q50/00

    CPC classification number: G06N5/04 ,  G06F16/9535 ,  G06N7/005 ,  G06Q50/01

    Abstract: At least one embodiment of this disclosure includes a method of inferring attribute labels for a user in a social networking system based on the user's social connections and user-specified attribute labels in the social networking system. The method can include: establishing variational equations based on attribute labels of nodes in an ego network in a social graph of a social networking system; determining likelihood scores for at least a portion of the attribute labels of neighboring nodes from a focal user node in the ego network based on user-specified attribute labels from the social networking system; and calculating probability distributions of possible attribute labels for the focal user node of the ego network based on the variational equations and the likelihood scores.

    STRIPING OF DIRECTED GRAPHS
    3.
    发明申请
    STRIPING OF DIRECTED GRAPHS 有权
    条纹图案

    公开(公告)号：US20160019313A1

    公开(公告)日：2016-01-21

    申请号：US14336363

    申请日：2014-07-21

    Applicant: Facebook, Inc.

    Inventor： Deepayan Chakrabarti ,  Jonathan Chang ,  Avery Li Kuang Ching ,  Maja Kabiljo

    IPC: G06F17/30 ,  H04L29/06 ,  H04L12/26 ,  H04L12/911

    CPC classification number: G06F17/30958 ,  G06F17/30336 ,  G06F17/30377 ,  G06Q50/01 ,  H04L47/70 ,  H04L65/403 ,  H04L67/1097

    Abstract: Embodiments are disclosed for striping a directed graph, e.g., a social graph, so as to efficiently perform an operation to each node in the directed graph. At least some of the embodiments can select first and second sets of nodes from the directed graph to form first and second stripes. The first and second sets of nodes are selected, for example, based on available computing resources. First and second intermediate results can be generated by performing the operation to each node of the first and the second stripes, respectively. The operation iteratively performs a superstep. The first and the second intermediate results are combined to form a collective result as an output of the superstep.

    Abstract translation: 公开了用于条带化有向图（例如，社交图）的实施例，以有效地对有向图中的每个节点执行操作。 至少一些实施例可以从有向图中选择第一和第二组节点以形成第一和第二条带。 例如，基于可用的计算资源来选择第一和第二组节点。 可以通过分别对第一和第二条纹的每个节点执行操作来生成第一和第二中间结果。 该操作迭代地执行一个超级步骤。 第一和第二中间结果被组合以形成作为超级步骤的输出的集合结果。

    STRIPING OF DIRECTED GRAPHS AND NODES WITH IMPROVED FUNCTIONALITY
    4.
    发明申请
    STRIPING OF DIRECTED GRAPHS AND NODES WITH IMPROVED FUNCTIONALITY 有权
    具有改进的功能的指导图和条纹的划线

    公开(公告)号：US20160203235A1

    公开(公告)日：2016-07-14

    申请号：US15077852

    申请日：2016-03-22

    Applicant: Facebook, Inc.

    Inventor： Deepayan Chakrabarti ,  Jonathan Chang ,  Avery Li Kuang Ching ,  Maja Kabiljo

    IPC: G06F17/30

    CPC classification number: G06F17/30958 ,  G06F17/30336 ,  G06F17/30377 ,  G06Q50/01 ,  H04L47/70 ,  H04L65/403 ,  H04L67/1097

    Abstract: Embodiments are disclosed for striping a directed graph, e.g., a social graph, so as to efficiently perform an operation to each node in the directed graph. At least some of the embodiments can select first and second sets of nodes from the directed graph to form first and second stripes. The first and second sets of nodes are selected, for example, based on available computing resources. First and second intermediate results can be generated by performing the operation to each node of the first and the second stripes, respectively. The operation iteratively performs a superstep. The first and the second intermediate results are combined to form a collective result as an output of the superstep.

    Abstract translation: 公开了用于条带化有向图（例如，社交图）的实施例，以有效地对有向图中的每个节点执行操作。 至少一些实施例可以从有向图中选择第一和第二组节点以形成第一和第二条带。 例如，基于可用的计算资源来选择第一和第二组节点。 可以通过分别对第一和第二条纹的每个节点执行操作来生成第一和第二中间结果。 该操作迭代地执行一个超级步骤。 第一和第二中间结果被组合以形成作为超级步骤的输出的集合结果。

    Selecting Users to Receive a Recommendation to Establish Connection to an Object in a Social Networking System
    5.
    发明申请
    Selecting Users to Receive a Recommendation to Establish Connection to an Object in a Social Networking System 审中-公开
    选择用户接收建立与社交网络系统中对象的连接的建议

    公开(公告)号：US20150142721A1

    公开(公告)日：2015-05-21

    申请号：US14083582

    申请日：2013-11-19

    Applicant: Facebook, Inc.

    Inventor： Deepayan Chakrabarti

    IPC: G06N7/00

    CPC classification number: G06N7/00 ,  G06Q30/0251 ,  G06Q50/01

    Abstract: A social networking system identifies users to receive a recommendation to establish a connection to an object maintained by the social networking system. The social networking system determines one or more classifiers identifying attributes of users to receive the recommendation based on attributes of users connected to the object and additional users connected to those users. The attributes of an additional user may be weighted by a factor that provides a measure of the overlap between the attributes of the additional user and a user connected to the object.

    Abstract translation: 社交网络系统识别用户接收建立与由社交网络系统维护的对象的连接的建议。 社交网络系统确定一个或多个识别用户属性的分类器，以基于连接到对象的用户的属性和连接到这些用户的附加用户的属性接收推荐。 附加用户的属性可以由提供附加用户的属性与连接到对象的用户之间的重叠的度量的因子加权。

    Semi-Supervised Learning via Deep Label Propagation
    7.
    发明申请
    Semi-Supervised Learning via Deep Label Propagation 审中-公开

    公开(公告)号：US20180336457A1

    公开(公告)日：2018-11-22

    申请号：US15597290

    申请日：2017-05-17

    Applicant: Facebook, Inc.

    Inventor： Aditya Pal ,  Deepayan Chakrabarti ,  Karthik Subbian ,  Anitha Kannan

    IPC: G06N3/08 ,  G06N3/04 ,  G06F17/30

    Abstract: In one embodiment, a system may access a graph data structure that includes nodes and connections between the nodes. Each node may be associated with a user; each connection between two nodes may represent a relationship between the associated users; and each node may be either labeled or unlabeled with respect to a label type. For each labeled node, a label of the label type of that labeled node may be propagated to other nodes through the connections. For each node, the system may store a label distribution information associated with the label type based on the propagated labels reaching the node. The system may train a machine-learning model using the labels and the label distribution information of a set of the labeled nodes. A predicted label for each unlabeled node may be generated using the model and the label distribution information of the unlabeled node.

    LABEL INFERENCE IN A SOCIAL NETWORK
    8.
    发明申请
    LABEL INFERENCE IN A SOCIAL NETWORK 有权
    社会网络中的标签语言

    公开(公告)号：US20150213370A1

    公开(公告)日：2015-07-30

    申请号：US14272176

    申请日：2014-05-07

    Applicant: Facebook, Inc.

    Inventor： Deepayan Chakrabarti ,  Sofus Attila Macskassy ,  Stanislav Funiak ,  Jonathan Chang

    IPC: G06N5/04 ,  G06Q50/00 ,  G06N7/00

    CPC classification number: G06N5/04 ,  G06F17/30867 ,  G06N7/005 ,  G06Q50/01

    Abstract: At least one embodiment of this disclosure includes a method of inferring attribute labels for a user in a social networking system based on the user's social connections and user-specified attribute labels in the social networking system. The method can include: establishing variational equations based on attribute labels of nodes in an ego network in a social graph of a social networking system; determining likelihood scores for at least a portion of the attribute labels of neighboring nodes from a focal user node in the ego network based on user-specified attribute labels from the social networking system; and calculating probability distributions of possible attribute labels for the focal user node of the ego network based on the variational equations and the likelihood scores.

    Abstract translation: 本公开的至少一个实施例包括一种在社交网络系统中基于用户的社交连接和用户指定的社交网络系统中的属性标签推断用户的属性标签的方法。 该方法可以包括：基于社交网络系统的社交图中的自我网络中的节点的属性标签来建立变分方程; 基于来自所述社交网络系统的用户指定的属性标签，确定所述自我网络中的焦点用户节点的至少一部分相邻节点的属性标签的可能性得分; 并且基于变分方程和似然分数来计算自我网络的焦点用户节点的可能属性标签的概率分布。

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