User to user recommender

• US 20070203790A1
• Filed: 12/19/2006
• Published: 08/30/2007
• Est. Priority Date: 12/19/2005
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Musicstrands Incorporated
• Inventors: Torrens, Marc, Ferrera, Pere
• Granted Patent: US 7,962,505 B2
• Time in Patent Office: Days
• US Class Current: 705/14.690
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising

Abstract

Disclosed are embodiments of systems and methods for recommending relevant users to other users in a user community. In one implementation of such a method, two different sets of data are considered: a) music (or other items) that users have been listening to (or otherwise engaging), and b) music (or other items) recommendations that users have been given. In some embodiments, pre-computation methods allow the system to efficiently compare item sets and recommended item sets among the users in the community. Such comparisons may also comprise metrics that the system can use to figure out which users should be recommended for a given target user.

Claims

1. A method for recommending users in a user community, the method comprising:

selecting a first user within the user community;

selecting a user set within the user community;

comparing a user profile for the first user with user profiles for each of the users in the user set; and

generating a recommended user set for the first user, wherein the recommended user set comprises at least one user within the user community.

2. The method of claim 1, wherein the recommended user set comprises a plurality of users within the user community.

3. The method of claim 1, wherein the step of selecting a first user comprises receiving a request from the first user to generate the recommended user set.

4. The method of claim 1, wherein the user set comprises each of the users in the user community.

5. The method of claim 1, wherein the user profile comprises a media item set including a plurality of media data items.

6. The method of claim 5, wherein the media data items comprise metadata identifying a plurality of media items.

7. The method of claim 5, wherein the step of generating a recommended user set comprises analyzing playcounts for media items in the media item set.

8. The method of claim 5, wherein the user profile further comprises a recommended media item set including a plurality of recommended media data items.

9. The method of claim 8, wherein the recommended user set is generated by using at least one of a metric that analyzes the intersection of the media item set with a media item set of media data items for each of the users in the user set, a metric that analyzes the intersection of the media item set with a recommended media item set of recommended media data items for each of the users in the user set, a metric that analyzes the intersection of the recommended media item set with a media item set of media data items for each of the users in the user set, and a metric that analyzes the intersection of the recommended media item set with a recommended media item set of recommended media data items for each of the users in the user set.

10. The method of claim 9, wherein the recommended user set is generated by further using playcounts for media items in the media item set for each of the users in the user set.

11. The method of claim 8, wherein the recommended user set is generated by using metric that analyzes the intersection of the media item set with a media item set of media data items for each of the users in the user set, a metric that analyzes the intersection of the media item set with a recommended media item set of recommended media data items for each of the users in the user set, a metric that analyzes the intersection of the recommended media item set with a media item set of media data items for each of the users in the user set, and a metric that analyzes the intersection of the recommended media item set with a recommended media item set of recommended media data items for each of the users in the user set.

12. A computer-readable medium having stored thereon computer executable instructions for performing a method for recommending users in a user community, the method comprising:

selecting a first user within the user community;

selecting a user set within the user community;

comparing a user profile for the first user with user profiles for each of the users in the user set; and

generating a recommended user set for the first user, wherein the recommended user set comprises at least one user within the user community.

13. The computer-readable medium of claim 12, wherein the step of selecting a first user comprises receiving a request from the first user to generate the recommended user set.

14. The computer-readable medium of claim 12, wherein the user profile comprises a media item set including a plurality of media data items.

15. The computer-readable medium of claim 14, wherein the media data items comprise metadata identifying a plurality of media items.

16. The computer-readable medium of claim 14, wherein the step of generating a recommended user set comprises analyzing playcounts for media items in the media item set.

17. The computer-readable medium of claim 14, wherein the user profile further comprises a recommended media item set of recommended media data items.

18. The computer-readable medium of claim 17, wherein the recommended user set is generated by using at least one of a metric that analyzes the intersection of the media item set with a media item set of media data items for each of the users in the user set, a metric that analyzes the intersection of the media item set with a recommended media item set of recommended media data items for each of the users in the user set, a metric that analyzes the intersection of the recommended media item set with a media item set of media data items for each of the users in the user set, and a metric that analyzes the intersection of the recommended media item set with a recommended media item set of recommended media data items for each of the users in the user set.

19. The computer-readable medium of claim 18, wherein the recommended user set is generated by further using playcounts for media items in the media item set for each of the users in the user set.

20. The computer-readable medium of claim 17, wherein the recommended user set is generated by using metric that analyzes the intersection of the media item set with a media item set of media data items for each of the users in the user set, a metric that analyzes the intersection of the media item set with a recommended media item set of recommended media data items for each of the users in the user set, a metric that analyzes the intersection of the recommended media item set with a media item set of media data items for each of the users in the user set, and a metric that analyzes the intersection of the recommended media item set with a recommended media item set of recommended media data items for each of the users in the user set.