TECHNIQUE FOR DEFINING FEATURES AND PREDICTING LIKELIHOOD OF ADOPTION OF THE SAME USING MACHINE LEARNING MODELS

    公开(公告)号:US20240340223A1

    公开(公告)日:2024-10-10

    申请号:US18295643

    申请日:2023-04-04

    CPC classification number: H04L41/145 H04L41/22

    Abstract: In one aspect, a method of identifying network features includes receiving a first-time definition of a feature, the feature representing a user query for analytics associated with the feature based on data collected on a plurality of devices in one or more networks, generating the analytics associated with the feature, determining, using a trained machine learning model, a likelihood of adoption of at least the feature by one or more users of the plurality of devices, wherein the trained machine learning model receives as input the first-time definition and provides, as output, the likelihood of adoption of at least the feature, and configuring a user interface on a terminal to provide a visualization of at least one of the likelihood of adoption of at least the feature and the analytics associated with the feature.

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