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AssigneeIntuit Inc.
InventorsKevin Michael Furbish, Kevin M. McCluskey, Peter E. Lubczynski
Estimating the term…
Systems and methods for predicting one or more field values using machine learning in a knowledge engineering (KE) data model are disclosed. An example method may include identifying a first field in the KE data model which lacks a value and for which one or more machine learning models are defined, the first field being associated with one or more dependent field, determining that each dependent field of the first field has a corresponding value in the KE data model, executing each of the one or more machine learning models to predict one or more values for the first field, selecting one of the one or more predicted values as the representative value of the first field, identifying one or more further fields in the KE data model for which the first field is a dependent field, none of the one or more further fields defining any machine learning models, and calculating values for one or more further fields based at least in part on the representative value of the first field.
A method of predicting values for one or more fields of a knowledge engineering (KE) data model, the method performed by one or more processors of a computing device associated with one or more machine learning models and comprising:
A computing device associated with one or more machine learning models, the computing device comprising:
The computing device of claim 17, wherein the metadata indicates at least an indication that the value of the first field was predicted, and a confidence level associated with the selected one of the predicted values.
A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the computing device to predict one or more field values using machine learning in a knowledge engineering (KE) data model by performing operations comprising:
Dependencies are inferred from the claim text.