TEXT-BASED MACHINE LEARNING EXTRACTION OF TABLE DATA FROM A READ-ONLY DOCUMENT

Abstract: embodiments of the disclosed technologies provide solutions for automatically reading digital electronic documents that contain tables and correctly extracting table data, rows and columns from the documents with high accuracy and high throughput. embodiments are capable of converting a table portion of a read-only document to a searchable, editable data record using text rectangle (tr)-level numerical data that indicates probabilities of trs belonging to canonicals and at least one convolutional neural network (cnn) that processes the tr-level numerical data to produce table-level numerical data.

Inventor(s): Hongyang Yu, Hanieh Borhanazad, Sandip Mandlecha

CPC Classification: G06F16/2282 ({Tablespace storage structures; Management thereof})

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