US 11,989,505 B2
Generating personalized digital design template recommendations
Anand Khanna, San Jose, CA (US); Oliver Brdiczka, San Jose, CA (US); and Alexandru Vasile Costin, Monte Sereno, CA (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Oct. 5, 2022, as Appl. No. 17/938,253.
Prior Publication US 2024/0119230 A1, Apr. 11, 2024
Int. Cl. G06F 40/186 (2020.01); G06F 40/30 (2020.01); G06N 3/08 (2023.01)
CPC G06F 40/186 (2020.01) [G06F 40/30 (2020.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
generating, for a user a creative segment classification;
determining geo-seasonal intent data for a plurality of digital design templates by segmenting seasonal digital design templates from non-seasonal digital design templates by:
generating a plurality of length vectors for the plurality of digital design templates that comprises export counts per geographic locale; and
identifying a seasonal digital design template based on determining a value from a length vector of the plurality of length vectors satisfies a predetermined threshold;
generating template classifications for theft plurality of digital design templates by utilizing a machine learning model to process the geo-seasonal intent data and creative intent;
identifying a subset of digital design templates of the plurality of digital design templates based on the template classifications, the geo-seasonal intent data and the creative segment classification of the user; and
providing, for display to the user within a graphical user interface, the subset of digital design templates as recommendations.