Personalized vehicle recommender system

A method of generating a vehicle recommendation for a driver, the method comprising:

• receiving driver profile data about a driver, wherein the driver profile data includes user-generated driver profile data and enriched profile data;
• wherein the user-generated driver profile data includes at least one driving location, at least one driving route, a driver age, a driver occupation, a current vehicle, a current vehicle ownership type, a past vehicle, and a past vehicle ownership type;
• wherein the enriched driver profile data includes an expected vehicle spend value and each of an average snowfall, an average altitude, road condition information, an average driving speed, and an estimated commute time;
• receiving vehicle attribute data regarding each vehicle class in a list of vehicle classes;
• receiving a list of vehicle attribute categories;
• generating a driver attribute target value for each vehicle attribute category based on the driver profile data;
• and
• providing the enriched driver profile data, the user-generated driver profile data, the vehicle attribute data, and the driver attribute target values as input data to a trained neural network to generate, by the trained neural network, at least one vehicle recommendation, wherein the trained neural network functions as a hybrid recommender system performing content-based filtering and collaborative filtering and wherein the neural network is trained on vehicle attribute data and driver profile data.

A method of generating a vehicle recommendation for a driver, the method comprising:

• storing a list of vehicle attribute categories;
• storing vehicle attribute data for each vehicle class in a list of vehicle classes, wherein the vehicle attribute data includes, for each vehicle class, a vehicle attribute value for each vehicle attribute category;
• storing user-generated driver profile data inputted by a driver, wherein the user-generated driver profile data includes at least one driving location, at least one driving route, a driver age, and a driver occupation, a current vehicle, a current vehicle ownership type, a past vehicle, a past vehicle ownership type, a current owned vehicle rating, and a past owned vehicle rating;
• storing location characteristic data and social characteristic data;
• generating enriched driver profile data by comparing the user-generated driver profile data to the location characteristic data and/or to the social characteristic data, wherein the enriched driver profile data includes an expected vehicle spend value and each of an average snowfall, an average altitude, road condition information, an average driving speed, and an estimated commute time;
• calculating a driver attribute target value for each vehicle attribute category in the list of vehicle attribute categories based on the driver profile data, which includes the enriched driver profile data and the user-generated driver profile data;
• and
• providing the enriched driver profile data, the user-generated driver profile data, the vehicle attribute data, and the driver attribute target values as input data to a trained neural network to generate at least one vehicle recommendation, wherein the trained neural network functions as a hybrid recommender system performing content-based filtering and collaborative filtering and wherein the neural network is trained on vehicle attribute data and driver profile data.