Inferring user preferences from an internet based social interactive construct

• US 9,349,099 B2
• Filed: 01/12/2015
• Issued: 05/24/2016
• 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:
  US14/595,016
• Publication Number:
  US 20150127597A1
• Time in Patent Office: 498 Days
• Field of Search: 706/52
• 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 system comprising:

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

access social graph information identifying one or more users connected to a particular user on a social graph;

identify preferences of the one or more users; and

determine preferences of the particular user, based on the identified preferences of the one or more users.

2. The system of claim 1, wherein the social graph is associated with an online social network.

3. The system of claim 1, wherein at least one of the one or more users is at least a predetermined number of degrees away from the particular user in the social graph.

4. The system of claim 1, wherein specific users of the one or more users that are in close proximity to the particular user on the social graph carry more weight in determining the preferences of the particular user.

5. The system of claim 1, wherein the recommendation module is configured to identify the preferences of the one or more users by:

accessing user preference profiles associated with the one or more users, the user preference profiles indicating the preferences of the one or more users.

6. The system of claim 1, wherein the recommendation module is further configured to:

generate a user preference profile indicating the preferences of the particular user, based on the identified preferences of the one or more users.

7. The system of claim 1, wherein the preferences of the one or more users include at least one of personal information and topical information related to interactions of the one or more users.

8. The system of claim 1, wherein the determined preferences of the particular user are used to target advertising to the particular user.

9. The system of claim 1, wherein the determined preferences of the particular user are used to share reviews with the particular user.

10. The system of claim 1, wherein the determined preferences of the particular user are used to recommend at least one of a product and a service to the particular user.

11. The system of claim 1, wherein the determined preferences of the particular user are used to aid in ranking search results for the particular user.

12. 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:

accessing social graph information identifying one or more users connected to a particular user on a social graph;

identifying preferences of the one or more users; and

determining preferences of the particular user, based on the identified preferences of the one or more users.

13. The storage medium of claim 12, wherein the social graph is associated with an online social network.

14. The storage medium of claim 12, wherein at least one of the one or more users is at least a predetermined number of degrees away from the particular user in the social graph.

15. The storage medium of claim 12, wherein users of the one or more users that are in close proximity to the particular user on the social graph carry more weight in determining the preferences of the particular user.

16. A computer-implemented method comprising:

accessing social graph information identifying one or more users connected to a particular user on a social graph;

identifying preferences of the one or more users; and

determining, one or more hardware processors, preferences of the particular user, based on the identified preferences of the one or more users.

17. The method of claim 16, wherein the social graph is associated with an online social network.

18. The method of claim 16, wherein at least one of the one or more users is at least a predetermined number of degrees away from the particular user in the social graph.

19. The method of claim 16, wherein users of the one or more users that are in close proximity to the particular user on the social graph carry more weight in determining the preferences of the particular user.

20. The method of claim 16, wherein the determined preferences of the particular user are used to target advertising to the particular user.