Invention Grant
- Patent Title: Automated non-native table representation annotation for machine-learning models
-
Application No.: US16848294Application Date: 2020-04-14
-
Publication No.: US11551146B2Publication Date: 2023-01-10
- Inventor: Xin Ru Wang , Douglas Ronald Burdick , Ioannis Katsis
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Ference & Associates LLC
- Main IPC: G06F40/00
- IPC: G06F40/00 ; G06N20/00 ; G06F16/22 ; G06F40/279 ; G06F40/169 ; G06V10/40 ; G06F40/177 ; G06Q10/10 ; G06V30/10

Abstract:
One embodiment provides a method, including: receiving two documents, one of the two documents having at least one table that includes the same information as a corresponding table in the other of the two documents, wherein (i) one of the two documents comprises the at least one table in an unstructured table representation and (ii) the other of the two documents comprises the at least one table in a structured table representation; identifying text elements within the at least one table in the unstructured table representation; matching the identified text elements with table elements within the at least one table in the structured table representation; and annotating the at least one table in the structured table representation based upon the matches between the table elements and text elements.
Public/Granted literature
- US20210319356A1 AUTOMATED NON-NATIVE TABLE REPRESENTATION ANNOTATION FOR MACHINE-LEARNING MODELS Public/Granted day:2021-10-14
Information query