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1. (US10325149) Systems and methods for automatically identifying document information

Office : United States of America
Application Number: 16122819 Application Date: 05.09.2018
Publication Number: 10325149 Publication Date: 18.06.2019
Grant Number: 10325149 Grant Date: 18.06.2019
Publication Kind : B1
IPC:
G06F 17/22
G06K 9/00
G06F 16/435
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
F
ELECTRIC DIGITAL DATA PROCESSING
17
Digital computing or data processing equipment or methods, specially adapted for specific functions
20
Handling natural language data
21
Text processing
22
Manipulating or registering by use of codes, e.g. in sequence of text characters
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
[IPC code unknown for G06F 16/435]
CPC:
G06F 16/435
G06K 9/00483
G06K 9/00463
G06K 9/00469
Applicants: Coupa Software Incorporated
Inventors: Mark Oliver Burch
Hanieh Borhanazad
Agents: Hickman Palermo Becker Bingham LLP
Priority Data:
Title: (EN) Systems and methods for automatically identifying document information
Abstract: front page image
(EN)

A computer-implemented method comprises defining a set of canonical features for a document type and a plurality of attributes for a canonical feature; identifying a set of text rectangles from an electronic document; obtaining a comparison set of reference document codifications, one of which comprising a plurality of canonical feature codifications, one of which comprising one or more attribute values for one or more of the plurality of attributes of one of the set of canonical features as the one canonical feature appears in the one reference document; for each current canonical feature of the set of canonical features: selecting a set of canonical feature codifications from the comparison set and identifying a match between one of the set of text rectangles and one of the set of canonical feature codifications; for each of the set of text rectangles, selecting one of the matching canonical feature codifications.