Identifying interest twins in an online community

• US 20080162431A1
• Filed: 12/28/2006
• Published: 07/03/2008
• Est. Priority Date: 12/28/2006
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Xu, Hao, Xu, Zhichen
• Granted Patent: US 8,166,058 B2
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Techniques are described for identifying one or more “interest twins” of a user. An interest twin of a user in another user that has demonstrated interests in items that are the same as or similar to the items in which the user has demonstrated an interest. Various techniques are described for reducing the overhead in interest twin determination operations. Once the interest twins for a user have been identified, the knowledge of the interest twins may be used in a variety of ways to enhance to experience of the user. For example, a mechanism may be provided which allows the user to see a list of items in which the user'"'"'s interest twins have indicated an interest.

Claims

1. A method for identifying members of an online community that have interests similar to other members of the online community, the method comprising:

determining whether a first user is an interest twin of a second user based on a comparison between first data about the first user and second data about the second user; and

determining whether the second user is an interest twin of the first user based on a comparison between third data about the second user and fourth data about the first user;

wherein the first data is a subset of the fourth data; and

wherein the third data is a subset of the second data.

2. The method of claim 1 wherein:

the second data includes information about private interest-actions performed by the second user;

the third data does not include said information about private interest-actions performed by the second user;

the fourth data includes information about private interest-actions performed by the first user; and

the first data does not include said information about private interest-actions performed by the first user.

3. The method of claim 2 wherein:

both the second data and the third data include information about public interest-actions performed by the second user; and

both the first data and the third data include information about public interest-actions performed by the first user.

4. The method of claim 1 further comprising:

determining whether the first user is in a social network of the second user; and

including information about social network visible interest-actions performed by the first user in said first data if and only if the first user is in the social network of the second user.

5. The method of claim 1 further comprising:

presenting to the first user information that identifies one or more interest twins, from the online community, that have been automatically determined for the first user by comparing interest-actions performed by the first user with interest-actions performed by other members of the online community; and

presenting to the second user information that identifies one or more interest twins, from the online community, that have been automatically determined for the second user by comparing interest-actions performed by the second user with interest-actions performed by other members of the online community.

6. The method of claim 5 further comprising presenting to the first user a list of items in which the one of more interest twins of the first user have demonstrated an interest.

25. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1.

26. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 2.

27. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 3.

28. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 4.

29. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 5.

30. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 6.

7. A method for identifying interest twins of a target user, the method comprising:

recording interest-events performed by members of an online community that includes said target user;

identifying a particular set of items in which the target user is interested;

for each item in the particular set of items, generating an individual item score for each member of a particular set of members of the online community based, at least in part, on the amount of interest that said each member has demonstrated in the item; and

determining a set of one or more interest twins for the target user based, at least in part, on said individual item scores.

8. The method of claim 7 wherein:

the items belong to categories; and

the individual item score, for an item, for each member of the particular set of members, is based, at least in part, on the amount of interest that said member has demonstrated in items that belong to the category to which the item belongs.

9. The method of claim 8 wherein the individual item score, for an item, for each member of the particular set of members, is based, at least in part, on the amount of interest that said member has demonstrated in items that belong to categories that are related to the category to which the item belongs.

10. The method of claim 7 wherein:

the particular set of items is a subset of items for which the target has performed interest-actions; and

the method includes identifying the subset of items by filtering the items for which the user has performed interest-actions based on a item filtering criteria.

11. The method of claim 7 wherein the particular set is a comparison set generated by filtering members of the online community based on a member filtering criteria.

12. The method of claim 7 wherein determining a set of one or more interest twins includes generating twin scores for a plurality of members of the online community based on individual item scores that were generated for the plurality of members.

13. The method of claim 10 wherein filtering the items based on the item filtering criteria includes filtering the items based, at least in part, on a general popularity of the items.

14. The method of claim 13 wherein:

the items are tags; and

the method further comprises determining the general popularity of the tags based, at least in part, on how many users have used the tags, and how many taggable items have been tagged with the tags.

15. The method of claim 13 wherein filtering the items based on the item filtering criteria further includes filtering the items based, at least in part, on how much interest the target user has demonstrated in the items.

16. The method of claim 11 further comprising determining how many members to include in the comparison set based, at least in part, on how much interest the target user has demonstrated in the item for which the comparison set is generated.

17. The method of claim 11 wherein further comprising determining how many members to include in the comparison set based, at least in part, on a general popularity level of the item for which the comparison set is generated.

18. The method of claim 17 further comprising:

establishing a relatively low maximum membership for comparison sets generated for relatively popular items; and

establishing a relatively high maximum membership for comparison sets generated for relatively unpopular items.

19. The method of claim 7 wherein the step of determining a set of one or more interest twins for the target user includes:

generating composite scores based on said individual item scores;

ranking members of the online community based on the composite scores; and

selecting the members that have the N highest ranks to be the interest twins for the target user.

20. The method of claim 19 further comprising:

storing data that indicates the members with the M highest ranks, where M is greater than N; and

considering only the members indicated in the stored data when performing a subsequent interest twin determination operation for the target user.

21. The method of claim 7 wherein the step of determining a set of one or more interest twins for the target user is based, at least in part, on which members of the online community are in a social network of the target user.

22. The method of claim 7 wherein the step of determining a set of one or more interest twins for the target user is based, at least in part, on reputation values associated with members of the online community.

23. The method of claim 7 further comprising determining a subset of members of the online community for which to determine interest twins based, at least in part, on the size of social networks associated with members of the online community.

24. The method of claim 7 further comprising determining a subset of members of the online community for which to determine interest twins based, at least in part, on the amount of interest-actions performed by members of the online community.

31. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 7.

32. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 8.

33. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 9.

34. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 10.

35. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 11.

36. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 12.

37. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 13.

38. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 14.

39. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 15.

40. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 16.

41. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 17.

42. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 18.

43. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 19.

44. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 20.

45. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 21.

46. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 22.

47. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 23.

48. A computer-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 24.