MACHINE-LEARNING MODEL GENERATION
    1.
    发明公开

    公开(公告)号:US20240282452A1

    公开(公告)日:2024-08-22

    申请号:US18653547

    申请日:2024-05-02

    CPC classification number: G16H50/20 G06N20/00 G06Q50/22 G16H10/60

    Abstract: A computer-implemented method for generating one or more summarizations of a large volume of feedback data includes obtaining the feedback data. The feedback data is provided from disparate sources. The method includes separating the feedback data into a set of sentences, generating feedback embeddings of the set of sentences by providing the set of sentences to a set of machine models, providing topic input data to the set of machine models, computing sentence similarity of the feedback embeddings, calculating an importance score for each sentence of the set of sentences, ranking the set of sentences according to their respective importance scores, selecting one or more subsets of the set of sentences to generate the one or more summarizations, generating a visual representation of the one or more summarizations, and displaying the visual representation in an interactive user interface.

    Systems and methods for machine-automated classification of website interactions

    公开(公告)号:US11366834B2

    公开(公告)日:2022-06-21

    申请号:US16923633

    申请日:2020-07-08

    Abstract: A system includes a processor and memory. The memory stores a model database including models and a classification database including classification scores corresponding to an input. The memory stores instructions for execution by the processor. The instructions include, in response to receiving a first input from a user device of a user, determining, for the first input, classification scores for classifications by applying the models to the first input. Each model determines one of the classification scores. The instructions include storing the classification scores as associated with the first input in the classification database and identifying the first input as within a first classification in response to a first classification score corresponding to the first classification exceeding a first threshold. The instructions include transmitting, for display on an analyst device, the first input based on the first classification to a first analyst queue associated with the first classification.

    SYSTEMS AND METHODS FOR MACHINE-AUTOMATED CLASSIFICATION OF WEBSITE INTERACTIONS

    公开(公告)号:US20220012267A1

    公开(公告)日:2022-01-13

    申请号:US16923633

    申请日:2020-07-08

    Abstract: A system includes a processor and memory. The memory stores a model database including models and a classification database including classification scores corresponding to an input. The memory stores instructions for execution by the processor. The instructions include, in response to receiving a first input from a user device of a user, determining, for the first input, classification scores for classifications by applying the models to the first input. Each model determines one of the classification scores. The instructions include storing the classification scores as associated with the first input in the classification database and identifying the first input as within a first classification in response to a first classification score corresponding to the first classification exceeding a first threshold. The instructions include transmitting, for display on an analyst device, the first input based on the first classification to a first analyst queue associated with the first classification.

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