Request management using machine learning models trained with synthetic data and pseudo-labeled data
AssigneeServiceNow, Inc.
InventorsOrlando Marquez, Hessam Amini, Patrice Bechard
Life of this patent
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Abstract
A first machine learning model is trained using a synthetic training dataset. The first machine learning model is used to predict a plurality of pseudo-labels corresponding to an unlabeled dataset associated with a specific group. At least a portion of the unlabeled dataset and their corresponding pseudo-labels are selected to form a pseudo-labeled dataset. A second machine learning model is trained using the pseudo-labeled dataset and the synthetic training dataset as an improved version of the first machine learning model.
Claims20
A method, comprising:
- training a first machine learning model using a synthetic training dataset;
- using the first machine learning model to predict a plurality of pseudo-labels corresponding to an unlabeled dataset associated with a specific group;
- selecting at least a portion of the unlabeled dataset and their corresponding pseudo-labels to form a pseudo-labeled dataset;
- and
- training a second machine learning model using the pseudo-labeled dataset and the synthetic training dataset as an improved version of the first machine learning model.
A system, comprising:
- a processor configured to:
- train a first machine learning model using a synthetic training dataset;
- use the first machine learning model to predict a plurality of pseudo-labels corresponding to an unlabeled dataset associated with a specific group;
- select at least a portion of the unlabeled dataset and their corresponding pseudo-labels to form a pseudo-labeled dataset;
- and
- train a second machine learning model using the pseudo-labeled dataset and the synthetic training dataset as an improved version of the first machine learning model;
- and
- a memory coupled to the processor and configured to provide the processor with instructions.
A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
- training a first machine learning model using a synthetic training dataset;
- using the first machine learning model to predict a plurality of pseudo-labels corresponding to an unlabeled dataset associated with a specific group;
- selecting at least a portion of the unlabeled dataset and their corresponding pseudo-labels to form a pseudo-labeled dataset;
- and
- training a second machine learning model using the pseudo-labeled dataset and the synthetic training dataset as an improved version of the first machine learning model.
Dependencies are inferred from the claim text.