System and Method for Extracting Table Data from Text Documents Using Machine Learning

A non-transitory computer-readable medium having computer-readable instructions stored thereon which, when executed by a computer system, cause the computer system to perform the steps of:

• electronically receiving at a computer system a document having one or more tables, each table having one or more whitespace features;
• processing the document using a first computer model executed by the computer system to classify each row of the one or more tables as a header row or a data row;
• processing the document using a second computer model executed by the computer system to classify each whitespace feature in each row conditional on classification of each row by the first computer model, the second computer model identifying whether a whitespace feature corresponds to information missing from the one or more tables;
• and
• generating an output of the classified whitespace features and storing the output in a digital file.

A system for electronically extracting table data from text documents using machine learning, comprising:

• a computer system for electronically receiving a document having one or more tables, each table having one or more whitespace features;
• an engine executed by the computer system, the engine:
• processing the document using a first computer model executed by the computer system to classify each row of the one or more tables as a header row or a data row;
• processing the document using a second computer model executed by the computer system to classify each whitespace feature in each row conditional on classification of each row by the first computer model, the second computer model identifying whether a whitespace feature corresponds to information missing from the one or more tables;
• and
• generating an output of the classified whitespace features and storing the output in a digital file.