Systems and methods for user platform based recommendations

A system, comprising:

• a memory storing processor readable instructions;
• and
• at least one processor configured to access the memory and execute the processor readable instructions, which when executed by the at least one processor, configures the at least one processor to perform a plurality of functions, including functions for:
• accessing a plurality of user platforms;
• identifying user-related content linked to the user via the user platforms;
• extracting user attributes based on the user-related content by:
• receiving user images associated with the user-related content;
• determining one or more image attributes of the user images, the one or more image attributes including content of the user images determined by performing image recognition on the user images;
• determining context associated with the user images;
• applying the one or more image attributes of the user images and the context associated with the user images to a machine-learning model, the machine-learning model trained to identify user attributes based on both the one or more image attributes of the user images and the context associated with the user images to output the user attributes;
• and
• receiving, from the machine-learning model, the outputted user attributes;
• applying weights to vehicle attributes in a vehicle grading engine, based on the outputted user attributes;
• generating the vehicle grades based on the weights;
• and
• providing the vehicle grades to the user via a vehicle grading platform.

A non-transitory computer readable storage medium storing instructions to control one or more processors to perform operations, including:

• accessing a plurality of user platforms;
• identifying user-related content linked to the user via the user platforms;
• extracting user attributes based on the user-related content by:
• receiving user images associated with the user-related content;
• determining one or more image attributes of the user images, the one or more image attributes including content of the user images determined by performing image recognition on the user images;
• determining context associated with the user images;
• applying the one or more image attributes of the user images and the context associated with the user images to a machine-learning model, the machine-learning model trained to identify user attributes based on both the one or more image attributes of the user images and the context associated with the user images to output the user attributes;
• and
• receiving, from the machine-learning model, the outputted user attributes;
• applying weights to vehicle attributes in a vehicle grading engine, based on the outputted user attributes;
• generating the vehicle grades based on the weights;
• and
• providing the vehicle grades to the user via a vehicle grading platform.