MACHINE LEARNING MODELS TO REDUCE ERRORS IN DOCUMENT EXTRACTION

Abstract

A method including extracting, by a machine learning model executing using an electronic document, data to create extracted data. An error checking controller is executed on the extracted data to identify erroneous data within the extracted data. A label for the erroneous data is generated by a label controller executing on the erroneous data. The label identifies a type of error of the erroneous data and a correction to the type of error. The label is added to the erroneous data to generate labeled erroneous data. A training controller executes iterative steps to train the machine learning model using the electronic document, the labeled erroneous data, and a first instruction to generate new extracted data. The trained machine learning model is returned. The trained machine learning model has a reduced data extraction error rate relative to the machine learning model prior to executing the training controller.

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