US 12,136,118 B2
Deep learning based visual compatibility prediction for bundle recommendations
Kumar Ayush, Stanford, CA (US); Ayush Chopra, Delhi (IN); Patel U. Govind, Gujrat (IN); Balaji Krishnamurthy, Nodia (IN); and Anirudh Singhal, Uttar Pradesh (IN)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Mar. 20, 2023, as Appl. No. 18/186,528.
Application 18/186,528 is a continuation of application No. 16/865,572, filed on May 4, 2020, granted, now 11,640,634.
Prior Publication US 2023/0316379 A1, Oct. 5, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/00 (2023.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06N 3/088 (2023.01); G06Q 30/0601 (2023.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01)
CPC G06Q 30/0631 (2013.01) [G06F 18/214 (2023.01); G06F 18/2193 (2023.01); G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01)] 20 Claims
OG exemplary drawing
 
1. One or more non-transitory computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising:
generating a compatibility score that quantifies visual compatibility between style of a partial outfit of items and style of a candidate item to add to the partial outfit based on feeding node embeddings, of items in the partial outfit generated by an encoder of a first neural network, into a second neural network comprising a style autoencoder to generate item style embeddings for the items and computing a style embedding for the partial outfit as a weighted combination of the item style embeddings, weighted based on pairwise similarities predicted by a decoder of the first neural network; and
performing one or more pre-determined actions based on the compatibility score.