Method and apparatus for aggregating user data and providing recommendations

• US 8,533,286 B2
• Filed: 04/30/2011
• Issued: 09/10/2013
• Est. Priority Date: 01/08/2007
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Mspot (Samsung Electronics Co. Ltd.)
• Inventors: Ho, Edwin, Wai, King Sun
• Primary Examiner(s): Beamer, Temica M
• Application Number:
  US13/098,404
• Publication Number:
  US 20110208831A1
• Time in Patent Office: 864 Days
• Field of Search: 455/414.1, 455/418, 455/419, 455/552.1, 455/556.1, 455/557, 709/217, 709/231, 709/233
• US Class Current: 709/217
• CPC Class Codes: G06F 16/178 Techniques for file synchronisation in file systems
• CPC Class Codes: H04L 12/189 in combination with wireless systems selective distribution or broadcast in wireless communication networks H04W4/06
• CPC Class Codes: H04L 67/04 specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/104 Peer-to-peer [P2P] networks
• CPC Class Codes: H04L 67/1068 Discovery involving direct consultation or announcement among potential requesting and potential source peers
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04N 21/25875 involving end-user authentication restricting access to computer systems by authenticating users using a predetermined code G06F21/33; arrangements for secret or secure communication including means for verifying the identity or authority of a user of the system H04L9/32; networks authentication protocols H04L63/08; authentication in wireless network security H04W12/06
• CPC Class Codes: H04N 21/41407 embedded in a portable device, e.g. video client on a mobile phone, PDA, laptop constructional details of equipment or arrangements specially adapted for portable computer application G06F1/1626; arrangements specially adapted for mobile receivers in broadcast systems H04H20/57
• CPC Class Codes: H04N 21/4825 using a list of items to be played back in a given order, e.g. playlists
• CPC Class Codes: H04N 21/8113 comprising music, e.g. song in MP3 format
• CPC Class Codes: H04N 5/765 Interface circuits between an apparatus for recording and another apparatus

Abstract

A method and system for aggregating user data and providing recommendations for digital content or in conjunction with a social network is disclosed.

Claims

1. A computing cloud comprising:

a social networking system providing a social network having multiple users;

a content store configured to store interaction data for at least one user of the social network, wherein said interaction data relates to digital content that said at least one user interacted with; and

a recommendation engine configured to provide a recommendation for digital content to a first user of the social network based upon interaction data for said first user, interaction data for at least one other user of the social network, and correlation information for said first user, wherein said correlation information comprises a correlation between pieces of digital content included in a playlist of said first user.

2. The apparatus of claim 1, wherein:

interaction data for at least one user of the social network comprises digital fingerprints for audio content that said at least one user interacted with; and

a recommendation for digital content comprises a recommendation for audio content.

3. The apparatus of claim 1, wherein:

for at least one user of the social network, the content store is further configured to;

store at least one playlist of said at least one user, wherein each playlist comprises one or more pieces of digital content;

maintain different types of digital content of said at least one user; and

collect metadata generated by said at least one user interacting with digital content when said at least one user uploads digital content to the content store; and

the recommendation engine store is further configured to;

determine said correlation information for said first user based on at least one playlist of said first user, wherein said correlation information comprises one or more correlations between pieces of digital content included in said at least one playlist.

4. The apparatus of claim 1, wherein interaction data for at least one user of the social network comprises metadata collected from a plurality of devices operated by said at least one user.

5. A computing cloud comprising:

a social networking system providing one or more social networks, wherein each social network has multiple users;

a content store configured to store interaction data for at least one user of said one or more social networks, wherein said interaction data relates to digital content that said at least one user interacted with; and

a recommendation engine configured to provide a recommendation to a first user of a first social network of said one or more social networks to add a different user to the first social network, wherein the recommendation is based upon interaction data for said first user, interaction data for said different user, and correlation information for said first user, wherein said correlation information comprises a correlation between pieces of digital content included in a playlist of said first user.

6. The computing cloud of claim 5, wherein interaction data for at least one user of said one or more social networks comprises digital fingerprints for audio content that said at least one user interacted with.

7. The computing cloud of claim 5, wherein interaction data for at least one user of said one or more social networks comprises metadata collected from a plurality of devices operated by said at least one user.

8. The computing cloud of claim 5, wherein:

the recommendation engine store is further configured to;

determine said correlation information for said first user based on at least one playlist of said first user, wherein said correlation information comprises one or more correlations between pieces of digital content included in said at least one playlist.

9. The computing cloud of claim 5, wherein:

for at least one user of said one or more social networks, the content store is further configured to;

store at least one playlist of said at least one user, wherein each playlist comprises one or more pieces of digital content;

maintain different types of digital content of said at least one user; and

collect metadata generated by said at least one user interacting with digital content when said at least one user uploads digital content to the content store.

10. A method for generating a recommendation, comprising:

storing interaction data for at least one user of a social network, wherein said interaction data relates to digital content that said at least one user interacted with; and

providing a recommendation for digital content to a first user of the social network based upon interaction data for said first user, interaction data for at least one other user of the social network, and correlation information for said first user, wherein said correlation information comprises a correlation between pieces of digital content included in a playlist of said first user.

11. The method of claim 10, wherein:

interaction data for at least one user of the social network comprises digital fingerprints for audio content that said at least one user interacted with; and

a recommendation for digital content comprises a recommendation for audio content.

12. The method of claim 10, further comprising:

obtaining social network information for said first user;

identifying said one or more other users of the social network based upon the social network information for said first user;

for at least one user of the social network;

storing at least one playlist of said at least one user, wherein each playlist comprises one or more pieces of digital content;

maintaining different types of digital content of said at least one user; and

collecting metadata generated by said at least one user interacting with digital content when said at least one user uploads digital content to the social network; and

determining said correlation information for said first user based on at least one playlist of said first user, wherein said correlation information comprises one or more correlations between pieces of digital content included in said at least one playlist.

13. The method of claim 10, wherein interaction data for at least one user of the social network comprises metadata collected from a plurality of devices operated by said at least one user.

14. A method for generating a recommendation, comprising:

storing interaction data for at least one user of said one or more social networks, wherein said interaction data relates to digital content that said at least one user interacted with; and

providing a recommendation to a first user of a first social network of said one or more social networks to add a different user to the first social network, wherein the recommendation is based upon interaction data for said first user, interaction data for said different user, and correlation information for said first user, wherein said correlation information comprises a correlation between pieces of digital content included in a playlist of said first user.

15. The method of claim 14, wherein interaction data for at least one user of said one or more social networks comprises digital fingerprints for audio content that said at least one user interacted with.

16. The method of claim 14, wherein interaction data for at least one user of said one or more social networks comprises metadata collected from a plurality of devices operated by said at least one user.

17. The method of claim 14, further comprising:

obtaining social network information for said first user; and

identifying said one or more other users of the social network based upon the social network information for said first user.

18. The method of claim 14, further comprising:

for at least one user of the social network;

storing at least one playlist of said at least one user, wherein each playlist comprises one or more pieces of digital content;

maintaining different types of digital content of said at least one user; and

obtaining metadata generated by said at least one user interacting with digital content when said at least one user uploads digital content to said one or more social networks; and

determining said correlation information for said first user based on at least one playlist of said first user, wherein said correlation information comprises one or more correlations between pieces of digital content included in said at least one playlist.

19. The method of claim 14, wherein interacting with digital content comprises listening to audio content on a mobile device.

20. The method of claim 19, wherein the audio content comprises a song.