US 12,499,135 B2
Computer systems and methods for identifying location entities and generating a location entity data taxonomy
Azadeh Yazdan Panah Gohar Rizi, Richmond Hill (CA); Matt Man, Thornhill (CA); Taylor Wasser, Toronto (CA); and Julian Clayton, Milford, CT (US)
Assigned to Procore Technologies, Inc., Carpinteria, CA (US)
Filed by Procore Technologies, Inc., Carpinteria, CA (US)
Filed on Sep. 30, 2022, as Appl. No. 17/957,501.
Prior Publication US 2024/0111792 A1, Apr. 4, 2024
Int. Cl. G06F 16/29 (2019.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 30/14 (2022.01); G06V 30/146 (2022.01); G06V 30/18 (2022.01); G06V 30/19 (2022.01); G06V 30/30 (2022.01); G06V 30/422 (2022.01)
CPC G06F 16/29 (2019.01) [G06V 10/82 (2022.01); G06V 30/14 (2022.01); G06V 30/1456 (2022.01); G06V 30/147 (2022.01); G06V 30/18181 (2022.01); G06V 30/19153 (2022.01); G06V 30/30 (2022.01); G06V 30/422 (2022.01); G06V 20/20 (2022.01)] 20 Claims
OG exemplary drawing
 
14. A method carried out by a computing platform, the method comprising:
obtaining a two-dimensional drawing of a portion of a construction project;
performing an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing;
deriving embeddings for each location entity in the two-dimensional drawing;
based on the derived embeddings, determining relationships between the one or more location entities; and
based on the determined relationships between the one or more location entities, generating a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity, wherein generating the location entity data taxonomy comprises applying one or more machine-learning models that are configured to receive the derived embeddings as input and output the location entity data taxonomy;
cause an end-user device to display a visualization of the location entity data taxonomy; and
cause the end-user device to filter the displayed visualization based on information about a given user associated with the end-user device.