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    EFFICIENT PROCESSING OF NEIGHBORHOOD DATA
    2.
    发明申请
    EFFICIENT PROCESSING OF NEIGHBORHOOD DATA 审中-公开

    公开(公告)号：US20190286754A1

    公开(公告)日：2019-09-19

    申请号：US16178443

    申请日：2018-11-01

    Applicant: Pinterest, Inc.

    Inventor： Jurij Leskovec ,  Chantat Eksombatchai ,  Kaifeng Chen ,  Ruining He ,  Rex Ying

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

    Abstract: Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.

    GENERATING NEIGHBORHOOD CONVOLUTIONS WITHIN A LARGE NETWORK
    5.
    发明申请
    GENERATING NEIGHBORHOOD CONVOLUTIONS WITHIN A LARGE NETWORK 审中-公开

    公开(公告)号：US20190286658A1

    公开(公告)日：2019-09-19

    申请号：US16273939

    申请日：2019-02-12

    Applicant: Pinterest, Inc.

    Inventor： Jurij Leskovec ,  Chantat Eksombatchai ,  Kaifeng Chen ,  Ruining He ,  Rex Ying

    IPC: G06F16/901 ,  G06F16/906 ,  G06K9/62 ,  G06F16/22 ,  G06F16/9536 ,  G06N20/00

    Abstract: Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.

    EFFICIENT CONVOLUTIONAL NETWORK FOR RECOMMENDER SYSTEMS
    9.
    发明申请
    EFFICIENT CONVOLUTIONAL NETWORK FOR RECOMMENDER SYSTEMS 审中-公开

    公开(公告)号：US20190286752A1

    公开(公告)日：2019-09-19

    申请号：US16101184

    申请日：2018-08-10

    Applicant: Pinterest, Inc.

    Inventor： Jurij Leskovec ,  Chantat Eksombatchai ,  Ruining He ,  Kaifeng Chen ,  Rex Ying

    IPC: G06F17/30 ,  G06N3/08 ,  G06N3/04 ,  G06K9/62

    Abstract: Systems and methods for generating embeddings for nodes of a corpus graph are presented. The embeddings correspond to aggregated embedding vectors for nodes of the corpus graph. Without processing the entire corpus graph to generate all aggregated embedding vectors, a relevant neighborhood of nodes within the corpus graph are identified for a target node of the corpus graph. Based on embedding information of the target node's immediate neighbors, and also upon neighborhood embedding information from the target node's relevant neighborhood, an aggregated embedding vector can be generated for the target node that comprises both an embedding vector portion corresponding to the target node, as well as a neighborhood embedding vector portion, corresponding to embedding information of the relevant neighborhood of the target node. Utilizing both portions of the aggregated embedding vector leads to improved content recommendation to a user in response to a query.

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