Ranking of asset tags
    1.
    发明授权

    公开(公告)号:US11303530B2

    公开(公告)日:2022-04-12

    申请号:US16822692

    申请日:2020-03-18

    Applicant: Kyndryl, Inc.

    Abstract: An embodiment includes calculating an efficacy value of a context assigned to an asset, the efficacy value being based at least in part on a percentage of assets assigned to the context. The embodiment also includes calculating, responsive to the calculated efficacy value being within a predetermined range, a normalized relevance value of a first tag associated with the asset. The embodiment also includes generating relative relevance value for the first tag and a reason code associated with a basis for the relative relevance value of the first tag based at least in part on the normalized relevance value of the first tag. The embodiment also includes initiating, responsive to generating the relative relevance value and the reason code for the first tag, a database command on a training dataset stored in the database that includes the first tag.

    System to Infer Longevity of Cloud Computing Resource Usage and Rank in Order of Importance

    公开(公告)号:US20250069003A1

    公开(公告)日:2025-02-27

    申请号:US18455435

    申请日:2023-08-24

    Applicant: Kyndryl, Inc.

    Abstract: An approach is disclosed that creates a network graph that identifies computing resources as nodes. Each of the computing resources is weighted based upon the corresponding resource's attributes and usage. The approach connects a first set of nodes as directly connected and a second set of nodes as indirectly connected. Node longevity values are calculated for each node in the network graph with each of the node longevity values corresponding to one of the nodes in the network graph. The calculations are based on the direct and indirect connections between each of the nodes. The computing resources are managed based on the corresponding node longevity values.

    CONTINUOUS MAINTENANCE OF MODEL EXPLAINABILITY

    公开(公告)号:US20240256916A1

    公开(公告)日:2024-08-01

    申请号:US18161191

    申请日:2023-01-30

    Applicant: KYNDRYL, INC.

    CPC classification number: G06N5/022

    Abstract: A computer-implemented method for model building with explainability is provided. The method includes receiving, by a hardware processor, a first metric and a second metric of minimum model performance. The first metric relates to data modeling quality and the second metric relates to model to business rule correlations. The method further includes performing, by the hardware processor, auto Artificial Intelligence model generation responsive to training data and a combination of the first and the second metrics of minimum model performance to obtain a model that is trained and meets model prediction accuracy and model prediction explainability requirements represented by the combination of the first and the second metrics of minimum model performance.

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