Inferring user preferences from an internet based social interactive construct

• US 9,355,361 B2
• Filed: 01/15/2015
• Issued: 05/31/2016
• 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:
  US14/598,146
• Publication Number:
  US 20150127585A1
• Time in Patent Office: 502 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:

receiving a request from a particular user to view one or more online reviews;

in response to receiving the request, accessing a plurality of reviews generated by a plurality of review authors;

determining, using one or more hardware processors, a similarity of one or more of the review authors to the particular user, based on at least one of a user preference profile of the particular user and a connection of the particular user on an online social network;

sorting the reviews, based on the determined similarity of the one or more of the review authors to the particular user; and

providing the sorted reviews to the particular user.

2. The method of claim 1, wherein a first review generated by a first review author determined to be similar to the particular user appears higher in the sorted reviews than a second review generated by a second review author determined to be dissimilar to the particular user.

3. The method of claim 1, wherein the similarity of a specific review author to the particular user is determined by:

comparing the user preference profile of the particular user and a second user preference profile of the specific review author, the user preference profile indicating preferences of the particular user and the second user preference profile indicating preferences of the specific review author; and

determining that the particular user is similar to the specific review author, based on a correspondence between the user preference profile and the second user preference profile.

4. The method of claim 1, wherein the similarity of a specific review author to the particular user is determined by:

determining a degree of connection between the specific review author and the particular user on the online social network; and

determining that the particular user is similar to the specific review author, based on the determined degree of connection.

5. The method of claim 1, wherein each of the plurality of reviews are associated with at least one of a venue, a service, and a location.

6. The method of claim 1, wherein the plurality of reviews are posted on the online social network.

7. The method of claim 1, wherein the review authors are members of the online social network.

8. The method of claim 1, wherein the plurality of reviews are posted on an ecommerce website.

9. A system comprising:

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

receive a request from a particular user to view one or more online reviews;

access a plurality of reviews generated by a plurality of review authors;

determine a similarity of one or more of the review authors to the particular user, based on at least one of a user preference profile of the particular user and a connection of the particular user on an online social network;

sort the reviews, based on the determined similarity of the one or more of the review authors to the particular user; and

provide the sorted reviews to the particular user.

10. The system of claim 9, wherein a first review generated by a first review author determined to be similar to the particular user appears higher in the sorted reviews than a second review generated by a second review author determined to be dissimilar to the particular user.

11. The system of claim 9, wherein the similarity of a specific review author to the particular user is determined by:

comparing the user preference profile of the particular user and a second user preference profile of the specific review author, the user preference profile indicating preferences of the particular user and the second user preference profile indicating preferences of the specific review author; and

determining that the particular user is similar to the specific review author, based on a correspondence between the user preference profile and the second user preference profile.

12. The system of claim 9, wherein the similarity of a specific review author to the particular user is determined by:

determining a degree of connection between the specific review author and the particular user on the online social network; and

determining that the particular user is similar to the specific review author, based on the determined degree of connection.

13. The system of claim 9, wherein each of the plurality of reviews are associated with at least one of a venue, a service, and a location.

14. The system of claim 9, wherein the plurality of reviews are posted on the online social network.

15. The system of claim 9, wherein the review authors are members of the online social network.

16. The system of claim 9, wherein the plurality of reviews are posted on an ecommerce website.

17. 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:

receiving a request from a particular user to view one or more online reviews;

accessing a plurality of reviews generated by a plurality of review authors;

determining a similarity of one or more of the review authors to the particular user, based on at least one of a user preference profile of the particular user and a connection of the particular user on an online social network;

sorting the reviews, based on the determined similarity of the one or more of the review authors to the particular user; and

providing the sorted reviews to the particular user.

18. The storage medium of claim 17, wherein a first review generated by a first review author determined to be similar to the particular user appears higher in the sorted reviews than a second review generated by a second review author determined to be dissimilar to the particular user.

19. The storage medium of claim 17, wherein the similarity of a specific review author to the particular user is determined by:

comparing the user preference profile of the particular user and a second user preference profile of the specific review author, the user preference profile indicating preferences of the particular user and the second user preference profile indicating preferences of the specific review author; and

determining that the particular user is similar to the specific review author, based on a correspondence between the user preference profile and the second user preference profile.

20. The storage medium of claim 17, wherein the similarity of a specific review author to the particular user is determined by:

determining a degree of connection between the specific review author and the particular user on the online social network; and

determining that the particular user is similar to the specific review author, based on the determined degree of connection.