Systems and methods for providing improved recommendations

Patent metadata

Field	Value
Publication number	US-2024185308-A1
Application number	US-202318526708-A
Country	US
Kind code	A1
Filing date	Dec 1, 2023
Priority date	Jul 13, 2018
Publication date	Jun 6, 2024
Grant date	—

Abstract

Systems and methods for providing improved recommendations are disclosed. In some embodiments, the systems and methods may be used for vehicle recommendations. The system may include a server system configured to receive user historical vehicle preferences, user vehicle preferences, generate weighted feature data sets, and apply a similarity model to the generated weighted feature data set in order to determine a vehicle recommendation data set. A visual representation of the vehicle recommendation data set may then be provided to an interface associated with a user.

First claim

1 - 20 . (canceled)

21 . A system for providing improved vehicle recommendations comprising:
a processor; non-volatile memory; and a set of instructions on the memory that are executable by the processor, configured for:
a user vehicle preference data input module configured to generate a user vehicle preference data set based on user input from a user interface on a user device, wherein the user vehicle preference data input module is further configured to provide, via the user interface, a questionnaire regarding vehicles;
a user historical vehicle preference data input module configured to generate a user historical vehicle preference data set based on an analysis of browsing history on the user interface;
a similarity cosine module configured to determine a vehicle recommendation data set, comprising at least one vehicle and its associated vehicle features, by minimizing a distance between a first vector and a plurality of second vectors representing a plurality of vehicles; and
providing the vehicle recommendation data set to the user device.

22 . The system of claim 21 , wherein the set of instructions further comprise receiving demographic information of the user; and
wherein the analysis of browsing history is based on other users' browsing history, wherein the other users match a demographic in the demographic information.

23 . The system of claim 21 , wherein the user vehicle preference data set comprises a plurality of data units corresponding to a plurality of vehicle features.

24 . The system of claim 23 , wherein the plurality of vehicle features comprise a make, model, mileage, location, optional features, and condition.

25 . The system of claim 21 , wherein the set of instructions further comprise a filter module configured to filter the vehicle recommendation data set based on one or more predetermined criteria.

26 . The system of claim 25 , wherein the one or more predetermined criteria comprise a maximum price.

27 . The system of claim 25 , wherein the one or more predetermined criteria comprise a requirement for each vehicle in the vehicle recommendation data set to comprise a unique combination of make and model.

28 . The system of claim 21 , wherein the user vehicle preference data set defines a first vector space and the user historical vehicle preference data set defines a second vector space, and wherein the first vector space and the second vector space have a different dimensionality.

29 . The system of claim 28 , wherein the set of instructions further comprise:
a mapping module configured to map the second vector space to the first vector space based on attributes of a predetermined threshold of vehicles viewed in the browsing history.

30 . The system of claim 21 , wherein the user vehicle preference data set comprises a field for every identified vehicle feature.

31 . A method for providing improved vehicle recommendations comprising:
receiving, by a user vehicle preference data input module, user vehicle preference data from a user interface on a user device wherein the user vehicle preference data input module is further configured to provide, via the user interface, a questionnaire regarding vehicles; determining, by a user historical vehicle preference data input module, user historical vehicle preference data based on an analysis of browsing history on the user interface; generating a first vector based on the user historical vehicle preference data in a vehicle feature space; determining, by a similarity cosine module, a vehicle recommendation data set, comprising at least one vehicle and its associated vehicle features, by minimizing a distance between the first vector and a plurality of second vectors representing a plurality of vehicles; and providing the vehicle recommendation data set to the user device.

32 . The method of claim 31 , further comprising receiving demographic information of the user; and
wherein the analysis of browsing history is based on other users' browsing history, wherein the other users match a demographic in the demographic information.

33 . The method of claim 31 , wherein the user vehicle preference data set comprises a plurality of data units corresponding to a plurality of vehicle features.

34 . The method of claim 33 , wherein the plurality of vehicle features comprises a make, model, mileage, location, optional features, and condition.

35 . The method of claim 31 , further comprising filtering, by a filter module, the vehicle recommendation data set based on one or more predetermined criteria.

36 . The method of claim 35 , wherein the one or more predetermined criteria comprise a maximum price.

37 . The method of claim 35 , wherein the one or more predetermined criteria comprise a requirement for each vehicle in the vehicle recommendation data set to comprise a unique combination of make and model.

38 . The method of claim 31 , wherein the user vehicle preference data set defines a first vector space and the user historical vehicle preference data set defines a second vector space, and wherein the first vector space and the second vector space have a different dimensionality.

39 . The method of claim 38 , further comprising:
mapping, by a mapping module, the second vector space to the first vector space based on attributes of a predetermined threshold of vehicles viewed in the browsing history.

40 . A non-transitory computer-readable medium storing a set of executable instructions comprising:
receiving, by a user vehicle preference data input module, user vehicle preference data from a user interface on a user device wherein the user vehicle preference data input module is further configured to provide, via the user interface, a questionnaire regarding vehicles; determining, by a user historical vehicle preference data input module, user historical vehicle preference data based on an analysis of browsing history on the user interface; generating a first vector based on the user historical vehicle preference data in a vehicle feature space; determining, by a similarity cosine module, a vehicle recommendation data set, comprising at least one vehicle and its associated vehicle features, by minimizing a distance between a first vector and a plurality of second vectors representing a plurality of vehicles; and providing the vehicle recommendation data set to the user device.

Assignees

• Capital One Services Llc

Inventors

• Anderson Jacob
• Venuraju Mithra Kosur
• Mittal Shilpa
• Hoang Ben
• Deshpande Amit
• Shen Jie

Classifications

• G06Q30/0278 Primary

  Product appraisal · CPC title

• G06F16/24578

  using ranking · CPC title

• G06F16/84

  Mapping; Conversion · CPC title

• G06F16/9535

  Search customisation based on user profiles and personalisation · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title