IP Library Granted Patent US 8,533,286
Granted Patent B2
US 8,533,286 · App. 13/098,404 · Granted Sep 10, 2013

Method and apparatus for aggregating user data and providing recommendations

Inventors: Edwin Ho (Palo Alto, CA); King Sun Wai (Castro Valley, CA)
Assignee: MSpot, Inc.
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Quick Facts
Patent No.
US 8,533,286
App. No.
13/098,404
Granted
Sep 10, 2013
Kind
B2
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 (60)

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.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 16, 2015
From: SAMSUNG RESEARCH AMERICA, INC.
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 034779/0914 →
CHANGE OF NAME Recorded Dec 18, 2014
From: SAMSUNG INFORMATION SYSTEMS AMERICA, INC.
To: SAMSUNG RESEARCH AMERICA, INC.
Reel/Frame 034674/0412 →
MERGER Recorded Apr 7, 2014
From: MSPOT, INC.
To: SAMSUNG INFORMATION SYSTEMS AMERICA, INC.
Reel/Frame 032622/0641 →
Continuity (6)
Continuation 12761313 · Apr 15, 2010
Continuation In Part 12355546 · Jan 16, 2009
Continuation In Part 11788711 · Apr 20, 2007
Provisional Application 61040131 · Mar 27, 2008
Provisional Application 60879416 · Jan 8, 2007
Related Publication 20110208831A1 · Aug 25, 2011