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    ACCESS POINT COORDINATION USING GRAPHS AND MACHINE LEARNING PROCESSES
    2.
    发明公开
    ACCESS POINT COORDINATION USING GRAPHS AND MACHINE LEARNING PROCESSES 审中-公开

    公开(公告)号：US20240267748A1

    公开(公告)日：2024-08-08

    申请号：US18166264

    申请日：2023-02-08

    Applicant: Cisco Technology, Inc.

    Inventor： Doosan Jung ,  Qixu Gong ,  Qihong Shao

    IPC: H04W16/20 ,  H04L41/16

    CPC classification number: H04W16/20 ,  H04L41/16 ,  H04W84/12

    Abstract: AP coordination, and more specifically intelligent AP coordination using a graph network and reinforcement learning may be provided. AP coordination may include translating a physical space into a logical space, wherein the physical space is being evaluated for AP coordination. A machine learning process may predict signal strengths of signals sent by one or more Access Points (APs) and received by one or more Stations (STAs), wherein the machine learning process uses the logical space, and wherein each STA is in a location of the physical space. One or more AP placements may be evaluated based on the signal strengths, and a recommended AP placement may be determined based on the evaluation.

    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK
    5.
    发明公开
    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK 审中-公开

    公开(公告)号：US20240135279A1

    公开(公告)日：2024-04-25

    申请号：US17973121

    申请日：2022-10-24

    Applicant: Cisco Technology, Inc.

    Inventor： Qixu Gong ,  Doosan Jung ,  Qihong Shao

    IPC: G06Q10/06

    CPC classification number: G06Q10/063118

    Abstract: Methods are provided in which a computing device obtains user data and network data associated with one or more assets used in an enterprise network of a user. The computing device further determines an identity of the user based on the user data and the network data and generates a task recommendation based on the identity of the user. The task recommendation includes one or more tasks having a plurality of operations that are to be performed within a predetermined time interval. The computing device further provides the task recommendation for performing one or more actions associated with configuring the enterprise network.

    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK
    6.
    发明公开
    PERSONAS DETECTION AND TASK RECOMMENDATION SYSTEM IN NETWORK 审中-公开

    公开(公告)号：US20240232747A9

    公开(公告)日：2024-07-11

    申请号：US17973121

    申请日：2022-10-25

    Applicant: Cisco Technology, Inc.

    Inventor： Qixu Gong ,  Doosan Jung ,  Qihong Shao

    IPC: G06Q10/06

    CPC classification number: G06Q10/063118

    Abstract: Methods are provided in which a computing device obtains user data and network data associated with one or more assets used in an enterprise network of a user. The computing device further determines an identity of the user based on the user data and the network data and generates a task recommendation based on the identity of the user. The task recommendation includes one or more tasks having a plurality of operations that are to be performed within a predetermined time interval. The computing device further provides the task recommendation for performing one or more actions associated with configuring the enterprise network.

    DETERMINING NETWORK-SPECIFIC USER BEHAVIOR AND INTENT USING SELF-SUPERVISED LEARNING
    7.
    发明公开
    DETERMINING NETWORK-SPECIFIC USER BEHAVIOR AND INTENT USING SELF-SUPERVISED LEARNING 审中-公开

    公开(公告)号：US20240179218A1

    公开(公告)日：2024-05-30

    申请号：US18072267

    申请日：2022-11-30

    Applicant: Cisco Technology, Inc.

    Inventor： Doosan Jung ,  Qihong Shao ,  Miriam Wagner Valladolid

    IPC: H04L67/50 ,  G06N20/00

    CPC classification number: H04L67/535 ,  G06N20/00

    Abstract: Methods are provided for generating recommendations related to a network domain by performing self-supervised machine learning using masked modeling of input data related to user interactions with the network domain and/or network related information. Specifically, a computing device obtains input data including one or more of network information indicative of a plurality of network devices in a network domain and user behavior information indicative of one or more user interactions with the network domain. The computing device performs a self-supervised machine learning using mask modeling of a plurality of elements that represent the input data, to determine contextual meaning of the input data and generating at least one actionable task related to the network domain based on the contextual meaning of the input data. The computing device further provides the at least one actionable task for performing one or more actions associated with the network domain.

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