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    Creating digital stories based on memory graphs and multi-turn dialogs for assistant systems
    1.
    发明授权
    Creating digital stories based on memory graphs and multi-turn dialogs for assistant systems 有权

    公开(公告)号：US12142298B1

    公开(公告)日：2024-11-12

    申请号：US18152064

    申请日：2023-01-09

    Applicant: Meta Platforms, Inc.

    Inventor： Satwik Kottur ,  Seungwhan Moon ,  Aram Markosyan ,  Hardik Shah

    IPC: G11B27/031 ,  G06F40/284 ,  G06F40/35 ,  G10L15/22 ,  G10L15/30 ,  G10L15/18

    Abstract: In one embodiment, a method includes receiving a first user request from a first user for generating a media montage from a client system during a dialog session with the first user, generating an initial media montage during the dialog session based on media collections associated with the first user, sending instructions for presenting the initial media montage to the client system during the dialog session, receiving a second user request from the first user from the client system during the dialog session for editing the initial media montage, generating an edited media montage from the initial media montage during the dialog session based on the second user request and a memory graph associated with the first user, and sending instructions for presenting the edited media montage to the client system during the dialog session.

    PREDICTING A FUTURE BEHAVIOR BY APPLYING A PREDICTIVE MODEL TO EMBEDDINGS REPRESENTING PAST BEHAVIORS AND THE FUTURE BEHAVIOR
    9.
    发明公开
    PREDICTING A FUTURE BEHAVIOR BY APPLYING A PREDICTIVE MODEL TO EMBEDDINGS REPRESENTING PAST BEHAVIORS AND THE FUTURE BEHAVIOR 审中-公开

    公开(公告)号：US20230334338A1

    公开(公告)日：2023-10-19

    申请号：US16024310

    申请日：2018-06-29

    Applicant: Meta Platforms, Inc.

    Inventor： Seungwhan Moon ,  Xiao Wu

    IPC: G06N3/08 ,  G06N5/02

    CPC classification number: G06N5/02 ,  G06N3/08

    Abstract: A system for user behavior prediction generates a first series of behavior event elements describing a first set of behaviors of one or more users, upon processing user interactions with an online system. In a first flow, the system generates a first series of time-distributed embeddings of the behavior event elements, and in a second flow parallel with the first flow, the system generates a proposed future embedding of a proposed future behavior of a user at a future time point subsequent to the first set of time points. Using a predictive model (e.g., a recursive neural network), the system transforms components of the first and second flows into an output describing plausibility of occurrence of the proposed future behavior of the user.

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