US 12,259,940 B2
Automation system and method
James A. Harding, Issaquah, WA (US); Anthony J. Paquin, Stuart, FL (US); Scott Thibault, Colchester, VT (US); and Jason A. Boatman, Charlottesville, VA (US)
Assigned to GROKIT DATA, INC., Stuart, FL (US)
Filed by Grokit Data, Inc., Stuart, FL (US)
Filed on Jul. 6, 2021, as Appl. No. 17/368,298.
Claims priority of provisional application 63/048,598, filed on Jul. 6, 2020.
Prior Publication US 2022/0005087 A1, Jan. 6, 2022
Int. Cl. G06F 16/00 (2019.01); G06F 3/0481 (2022.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06F 9/54 (2006.01); G06F 11/3604 (2025.01); G06F 16/80 (2019.01); G06F 16/84 (2019.01); G06F 16/951 (2019.01); G06F 16/955 (2019.01); G06F 16/957 (2019.01); G06F 16/958 (2019.01); G06F 18/214 (2023.01); G06F 40/14 (2020.01); G06N 5/02 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2023.01); G06Q 10/0631 (2023.01); G06Q 10/0633 (2023.01); G06Q 10/0637 (2023.01); G06Q 10/067 (2023.01); G06Q 30/0201 (2023.01); G06Q 30/0282 (2023.01); G06Q 30/0601 (2023.01); G06Q 10/083 (2023.01); G06Q 10/0833 (2023.01); G06Q 10/10 (2023.01); G06Q 30/04 (2012.01)
CPC G06F 16/958 (2019.01) [G06F 3/0481 (2013.01); G06F 9/4806 (2013.01); G06F 9/4843 (2013.01); G06F 9/485 (2013.01); G06F 9/5066 (2013.01); G06F 9/542 (2013.01); G06F 9/547 (2013.01); G06F 11/3612 (2013.01); G06F 11/3616 (2013.01); G06F 16/80 (2019.01); G06F 16/84 (2019.01); G06F 16/951 (2019.01); G06F 16/955 (2019.01); G06F 16/9577 (2019.01); G06F 16/986 (2019.01); G06F 18/214 (2023.01); G06F 40/14 (2020.01); G06N 5/027 (2013.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/0633 (2013.01); G06Q 10/06375 (2013.01); G06Q 10/067 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0282 (2013.01); G06Q 30/0641 (2013.01); G06Q 10/0833 (2013.01); G06Q 10/0838 (2013.01); G06Q 10/10 (2013.01); G06Q 30/04 (2013.01)] 27 Claims
OG exemplary drawing
 
1. A computer-implemented method, executed on a computing device, comprising:
providing a plurality of data description models corresponding to a plurality of websites to a machine learning process;
providing ontology data concerning the plurality of websites to the machine learning process, wherein the ontology data is a predefined dataset with normalized descriptors for a plurality of associated descriptors from the plurality of websites;
providing target website data concerning a target website to the machine learning process; and
processing the plurality of data description models, ontology data and target website data using the machine learning process to generate a data description model for the target website by processing the plurality of data description models and ontology data as training data for the machine learning process and processing the target website using the trained machine learning process to generate the data description model for the target website.