CONSUMER, RETAILER AND SUPPLIER COMPUTING SYSTEMS AND METHODS

• US 20130124361A1
• Filed: 01/05/2013
• Published: 05/16/2013
• Est. Priority Date: 07/08/2010
• Status: Abandoned Application

• Current Assignee: Christopher Bryson
• Original Assignee: Christopher Bryson
• Inventors: Bryson, Christopher
• Application Number:
  US13/734,959
• Publication Number:
  US 20130124361A1
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A system and method for generating recommendations is disclosed. The system includes first and second client machines, a connection router connected to the first and second client machines, at least one database, and at least one server connected to the connection router and in communication with the at least one database. The method involves generating and providing a list of recommendations.

Claims

1. A system for generating recommendations, the system comprising:

first and second client machines;

a connection router connected to the first and second client machines;

at least one database for storing the product information associated with a plurality of products, account information associated with a first account profile, and account information associated with a second account profile;

at least one server connected to the connection router and in communication with the at least one database, the at least one server operably configured to;

receive the product information from the at least one database;

generate a plurality of weighted values for each product based on the product information;

receive the account information associated with the first account profile;

select a set of products from the plurality of products based on the account information associated with the first account profile;

receive at least one survey result from the second client machine;

assign a matching value to a product from the set of products wherein the matching value is based on the plurality of weighted values and the at least one survey result;

generate a subset of products wherein the matching value of each product in the subset of products falls within a first predetermined range of values;

assign a similarity coefficient between the first account profile and the second account profile;

receive at least one recommendation associated with the second account profile from the at least one database if the similarity coefficient is within a second predetermined range of values; and

provide a list of recommendations to the first client machine, the list of recommendations comprising;

the at least one recommendation associated with the second account if the similarity coefficient is within the second predetermined range of values; and

the subset of products.

2. The system of claim 1, wherein the at least one server is further configured to:

identify conflicting products based on the account information; and

exclude the conflicting products from the set of products.

3. The system of claim 2, wherein the at least one server is operably configured to identify the conflicting products based on an objective metric.

4. The system of claim 3, wherein the objective metric is associated with a presence of an ingredient.

5. The system of claim 1, wherein the at least one server is operably configured to select the set of products from the plurality of products based on a purchase history of the first account profile.

6. The system of claim 1, wherein the at least one server is further configured to:

change the matching value based on input received from the first client machine; and

store the changed matching value in the product information.

7. The system of claim 1, wherein the first predetermined range is open and greater than a matching threshold.

8. The system of claim 1, wherein the second predetermined range is open and greater than a similarity threshold.

9. The system of claim 1, wherein the at least one server is operably configured to assign a similarity coefficient by calculating a Jaccard similarity coefficient based on the account information of the first account profile and the account information of the second account profile.

10. A method for generating a recommendation at a server, the method comprising:

receiving product information associated with a plurality of products, the product information being stored in at least one database;

generating a plurality of weighted values for each product based on the product information;

receiving account information associated with a first account profile stored in the at least one database;

selecting a set of products from the plurality of products based on the account information associated with a first account profile;

receiving at least one survey result from a client machine;

assigning a matching value to a product from the set of products wherein the matching value is based on the plurality of weighted values and the at least one survey result;

generating a subset of products wherein the matching value of each product in the subset of products falls within a first predetermined range of values;

assigning a similarity coefficient between the first account and a second account;

receiving at least one recommendation associated with the second account profile if the similarity coefficient is within a second predetermined range of values; and

providing a list of recommendations, the list of recommendations comprising;

the at least one recommendation associated with the second account if the similarity coefficient is within the second predetermined range of values; and

the subset of products.

11. The method of claim 10, further comprising identifying conflicting products based on the account information, wherein the set of products excludes the conflicting products.

12. The method of claim 11, wherein identifying the conflicting products comprises identifying based on an objective metric.

13. The method of claim 12, wherein the objective metric is associated with a presence of an ingredient.

14. The method of claim 10, wherein selecting the set of products comprises selecting the set of products from the plurality of products based on a purchase history of the first account profile.

15. The method of claim 10, further comprising:

changing the matching value based on input received from the client machine; and

storing the changed matching value in the product information.

16. The method of claim 10, wherein the first predetermined range is open and greater than a matching threshold.

17. The method of claim 10, wherein the second predetermined range is open and greater than a similarity threshold.

18. The method of claim 10, wherein assigning a similarity coefficient comprises calculating a Jaccard similarity coefficient based on the account information of the first account profile and account information of the second account profile.