Inferring user preferences from an internet based social interactive construct

• US 9,245,230 B2
• Filed: 01/15/2015
• Issued: 01/26/2016
• Est. Priority Date: 11/02/2007
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Pinckney, Thomas, Dixon, Christopher, Gattis, Matthew Ryan
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US14/598,141
• Publication Number:
  US 20150127598A1
• Time in Patent Office: 376 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

In embodiments of the present invention improved capabilities are described for a computer program product embodied in a computer readable medium that, when executing on one or more computers, helps determine an unknown user'"'"'s preferences through the use of internet based social interactive graphical representations on a computer facility by performing the steps of (1) ascertaining preferences of a plurality of users who are part of an internet based social interactive construct, wherein the plurality of users become a plurality of known users; (2) determining the internet based social interactive graphical representation for the plurality of known users; and (3) inferring the preferences of an unknown user present in the internet based social interactive graphical representation of the plurality of known users based on the interrelationships between the unknown user and the plurality of known users within the graphical representation.

Claims

1. A computer-implemented method comprising:

comparing a first user preference profile of a first user and a second user preference profile of a second user, the first user preference profile indicating preferences of the first user and the second user preference profile indicating preferences of the second user;

determining, using one or more hardware processors, that the first user is similar to the second user, based on the comparison;

identifying one or more recommendations associated with the second user; and

providing the recommendations to the first user.

2. The method of claim 1, further comprising:

identifying the preferences of the second user; and

generating the second user preference profile indicating the preferences of the second user.

3. The method of claim 2, wherein the preferences of the second user are identified based on search result selections of the second user.

4. The method of claim 2, wherein the preferences of the second user are identified by analyzing user actions of the second user on an online social network.

5. The method of claim 2, wherein the preferences of the second user are identified by crawling, from a third party website, information describing the preferences of the second user.

6. The method of claim 1, further comprising:

receiving a search query from the first user;

generating search results, based on the search query;

accessing search result selections of the second user;

ranking the search results, based on the search result selections of the second user; and

providing the ranked search results to the first user.

7. The method of claim 1, further comprising:

providing, to the first user, information indicating that the second user is similar to the first user and that the second user is a member of an online social network.

8. The method of claim 1, further comprising:

sorting a list of reviews including a review by the second user, based on the determination that the first user is similar to the second user; and

providing the sorted list of reviews to the first user.

9. The method of claim 1, wherein the recommendation is for at least one of a product and a service.

10. A system comprising:

a recommendation module, comprising one or more hardware processors, configured to;

compare a first user preference profile of a first user and a second user preference profile of a second user, the first user preference profile indicating preferences of the first user and the second user preference profile indicating preferences of the second user;

determine that the first user is similar to the second user, based on the comparison;

identify one or more recommendations associated with the second user; and

provide the recommendations to the first user.

11. The system of claim 10, wherein the recommendation module is further configured to:

identify the preferences of the second user; and

generate the second user preference profile indicating the preferences of the second user.

12. The system of claim 11, wherein the preferences of the second user are identified based on search result selections of the second user.

13. The system of claim 11, wherein the preferences of the second user are identified by analyzing user actions of the second user on an online social network.

14. The system of claim 11, wherein the preferences of the second user are identified by crawling, from a third party website, information describing the preferences of the second user.

15. The system of claim 10, wherein the recommendation module is further configured to:

receive a search query from the first user;

generate search results, based on the search query;

access search result selections of the second user;

rank the search results, based on the search result selections of the second user; and

provide the ranked search results to the first user.

16. The system of claim 10, wherein the recommendation module is further configured to:

provide, to the first user, information indicating that the second user is similar to the first user and that the second user is a member of an online social network.

17. The system of claim 10, wherein the recommendation module is further configured to:

sort a list of reviews including a review by the second user, based on the determination that the first user is similar to the second user; and

provide the sorted list of reviews to the first user.

18. The system of claim 10, wherein the recommendation is for at least one of products and services.

19. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:

comparing a first user preference profile of a first user and a second user preference profile of a second user, the first user preference profile indicating preferences of the first user and the second user preference profile indicating preferences of the second user;

determining that the first user is similar to the second user, based on the comparison;

identifying one or more recommendations associated with the second user; and

providing the recommendations to the first user.

20. The storage medium of claim 19, wherein the preferences of the second user are identified by analyzing user actions of the second user on an online social network.