Patent ID: 11921681
Assignee: OPTUM TECHNOLOGY, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. The system of claim 8, wherein the one or more processors, are further configured to:
for each table column:
generate, using a header-based table classification machine learning model of a plurality of classification machine learning models and based at least in part on a table column name set for the table column, a predicted header-based column type of a plurality of predicted column types for the table column and a header-based column type voting weight of a plurality of column type voting weights for the predicted header-based column type;
generate, using a data-based table classification machine learning model of the plurality of classification machine learning models and based at least in part on a table column value set for the table column, a predicted data-based column type of the plurality of predicted column types for the table column and a data-based column type voting weight of the plurality of column type voting weights for the predicted data-based column type;
generate, using an entity recognition classification machine learning model of the plurality of classification machine learning models and based at least in part on the table column value set, a predicted entity-recognition-based column type of the plurality of predicted column types for the table column and an entity-recognition-based column type voting weight of the plurality of column type voting weights for the predicted entity- recognition-based column type;
generate, using a pattern matching classification machine learning model of the plurality of classification machine learning models and based at least in part on the table column name set, a predicted pattern-machine-based column type of the plurality of predicted column types for the table column and a pattern-matching-based column type voting weight of the plurality of column type voting weights for the predicted entity- recognition-based column type; and
generate, using a voting machine learning model and based at least in part on the plurality of predicted column types and the plurality of column type voting weights, an overall column type prediction for the table column; and

initiate the performance of one or more second prediction-based actions based at least in part on each overall column type prediction for a table column.