US 12,093,839 B2
Entity learning recognition
Gaurav Goswami, New Deli (IN); Sharathchandra Umapathirao Pankanti, Yorktown Heights, NY (US); and Nalini K. Ratha, Yorktown Heights, NY (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Apr. 29, 2021, as Appl. No. 17/243,786.
Application 17/243,786 is a division of application No. 15/472,837, filed on Mar. 29, 2017, granted, now 11,093,796.
Prior Publication US 2021/0248424 A1, Aug. 12, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 5/022 (2023.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01)
CPC G06N 5/022 (2013.01) [G06F 18/2148 (2023.01); G06F 18/217 (2023.01); G06N 20/00 (2019.01); G06V 10/7747 (2022.01); G06V 10/776 (2022.01)] 9 Claims
OG exemplary drawing
 
1. A computer-implemented entity learning recognition training method, comprising:
in the training phase:
selecting a structural element from a plurality of structural elements;
for an entity comprising a language structure in a training database:
associating the structural element with an attribute in an aspect of the entity;
generating an augmented entity based on a combination of the structural element and the attribute; and
adding the augmented entity to the training database which creates an augmented database; and
training a model based on a combination of the original entity and the augmented entity in the augmented database.