Machine learning based end-to-end extraction of tables from electronic documents

An apparatus, comprising:

• a memory;
• and
• a processor operatively coupled to the memory, the processor configured to:
• receive a first electronic document and information on a character bounding box from a plurality of character bounding boxes and for each character from a plurality of characters in the first electronic document,
• identify, based on the plurality of character bounding boxes, a plurality of word bounding boxes, each word bounding box from the plurality of word bounding boxes associated with a word from a plurality of words in the first electronic document,
• determine, based on locations of the plurality of word bounding boxes, white space in a horizontal dimension of the first electronic document to identify a plurality of rows of a table included in the first electronic document, each row from the plurality of rows (1) including a set of words from the plurality of words and (2) being divided into a plurality of cells separated by the white space in the horizontal dimension,
• determine, using a machine learning algorithm, a class from a set of classes for each row from the plurality of rows in the table,
• extract, for each row from a subset of rows from the plurality of rows and based on the class from the set of classes for that row, a first set of word values associated with a set of words included in that row,
• generate a second electronic document based on (1) the first set of word values in each row from the subset of rows, (2) a second set of word values associated with a set of words included in remaining rows from the plurality of rows, (3) the plurality of rows of the table, (4) the plurality of columns of the table, (5) the white space in the horizontal dimension, and (6) white space in a vertical dimension such that the plurality of words in the table are computer-readable in the second electronic document, the remaining rows from the plurality of rows being different from the subset of rows from the plurality of rows.

A processor-readable non-transitory medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to:

• receive a first electronic document and locations of a plurality of character bounding boxes for each character from a plurality of characters in the first electronic document;
• identify, based on the locations of the plurality of character bounding boxes, a plurality of word bounding boxes, each word bounding box from the plurality of word bounding boxes associated with a word from a plurality of words in the first electronic document, the first electronic document including a table having a set of table cells positioned in a set of rows and a set of columns;
• identify, based on coordinates of the plurality of word bounding boxes, locations of horizontal white space between two adjacent rows from the set of rows;
• determine, using a machine learning algorithm and based on the locations of horizontal white space, a class from a set of classes for each row from the set of rows in the table;
• extract a set of table cell values associated with the set of table cells;
• and
• generate a second electronic document including the set of table cell values arranged in the set of rows and the set of columns and based on (1) the locations of horizontal white space, (2) locations of vertical white space, such that the plurality of words in the table are computer-readable in the second electronic document.