US 12,475,501 B2
Systems and methods for vehicle recommendations based on user gestures
Chih-Hsiang Chow, Plano, TX (US); Steven Dang, Plano, TX (US); and Elizabeth Furlan, Plano, TX (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Jul. 27, 2023, as Appl. No. 18/360,144.
Application 18/360,144 is a continuation of application No. 17/313,219, filed on May 6, 2021, granted, now 11,756,099.
Application 17/313,219 is a continuation of application No. 16/745,960, filed on Jan. 17, 2020, granted, now 11,010,815, issued on May 18, 2021.
Prior Publication US 2023/0368269 A1, Nov. 16, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/00 (2023.01); G06F 3/01 (2006.01); G06Q 30/0601 (2023.01); G06V 40/20 (2022.01)
CPC G06Q 30/0631 (2013.01) [G06F 3/017 (2013.01); G06Q 30/0629 (2013.01); G06Q 30/0643 (2013.01); G06V 40/20 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A computer-implemented method for providing an item recommendation based on user gesture, the method comprising:
receiving, by one or more processors, a gesture from a user performed on a displayed first content item;
generating, by the one or more processors, a second display of the first content item comprising a marking of the gesture by the user;
determining, by the one or more processors, a feature of the item based on a location of the gesture on a display of the first content item;
determining a preference value for the feature based on a comparison of the gesture to predetermined gestures associated with different preference values;
determining, by the one or more processors and via a machine learning algorithm, an item preference of the user based on one or more of the gesture, the feature of the item, or the preference value;
identifying, by the one or more processors, an item recommendation based on the item preference of the user;
determining a similarity level of the item recommendation by comparing the item recommendation to the item preference of the user;
determining whether the similarity level of the item recommendation is equal to or exceeds a predetermined threshold; and
outputting, by the one or more processors, the item recommendation to the user, the output including a display of the item recommendation and an indicator of the similarity level when the similarity level of the item recommendation is equal to or exceeds the predetermined threshold.