IP Library Granted Patent US 9,799,081
Granted Patent B1
US 9,799,081 · App. 14/231,179 · Granted Oct 24, 2017

Content recommendation platform

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Quick Facts
Patent No.
US 9,799,081
App. No.
14/231,179
Granted
Oct 24, 2017
Kind
B1
Abstract

A method for recommending content is disclosed. The method includes identifying social relationship data for a user, the social relationship data including a set of associated users, determining a subset of the set of associated users based on similarity of content item interaction on a content sharing server, and providing the subset of associated users as recommended users to follow by the user. The method also includes receiving an indication of a selection of users from the subset of associated users, originating a social content item recommendation list for the user based on the selected users, and providing the social content item recommendation list to the user.

Claims (72)

1. A method comprising:

identifying, by a processing device, social relationship data for a user, the social relationship data comprising a set of associated users;

determining, by the processing device, a subset of the set of associated users based on similarity between content item interactions of the associated users and content interactions of the user on a content sharing server;

providing, by the processing device, the subset of associated users as recommended users to follow by the user;

receiving, by the processing device, an indication of a selection of users from the subset of associated users;

originating, by the processing device, a social content item recommendation list for the user based on the selected users; and

providing, by the processing device, the social content item recommendation list to the user.

2. The method of claim 1 , wherein the subset of associated users is determined based on at least one of current subscriptions of the user or an activity history of the user on the content sharing server.

3. The method of claim 1 , wherein determining the subset of associated users comprises:

determining content items on the content sharing server with an interaction by the user;

for each content item viewed by the user, determining other users of the set of associated users that had an interaction with the content item to determine an affinity score for each user; and

selecting users for the subset of users with an affinity score that exceeds a threshold.

4. The method of claim 1 , wherein the user is also a member of an online social network separate from the content sharing server, and wherein the social relationship data is determined based on connections of the user on the social network to other users of the social network.

5. The method of claim 1 , wherein the social relationship data is determined from an address book of the user.

6. The method of claim 1 , further comprising generating a subscription to the selected users on the content sharing server.

7. A method comprising:

identifying, by a processing device, social relationship data for a user, the social relationship data comprising a set of associated users;

determining, by the processing device, a subset of the set of associated users based on similarity of content item interaction on a content sharing server;

using, by the processing device, content items associated with the subset of associated users to originate a social content item recommendation list for the user; and

providing the social content item recommendation list to the user.

8. The method of claim 7 , wherein the subset of associated users is determined based on at least one of current subscriptions of the user or an activity history of the user on the content sharing server.

9. The method of claim 7 , wherein determining the subset of associated users comprises:

determining content items on the content sharing server with an interaction by the user;

for each content item viewed by the user, determining other users of the set of associated users that had an interaction with the content item to determine an affinity score for each user; and

selecting users for the subset of users with an affinity score that exceeds a threshold.

10. The method of claim 7 , wherein the user is also a member of an online social network separate from the content sharing server, and wherein the social relationship data is determined based on connections of the user on the social network to other users of the social network.

11. The method of claim 7 , wherein the social relationship data is determined from an address book of the user.

12. A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to perform operations comprising:

identifying social relationship data for a user, the social relationship data comprising a set of associated users;

determining a subset of the set of associated users based on similarity of content item interaction on a content sharing server;

providing the subset of associated users as recommended users to follow by the user;

receiving an indication of a selection of users from the subset of associated users;

originating a social content item recommendation list for the user based on the selected users; and

providing the social content item recommendation list to the user.

13. The non-transitory machine-readable storage medium of claim 12 , wherein the subset of associated users is determined based on at least one of current subscriptions of the user or an activity history of the user on the content sharing server.

14. The non-transitory machine-readable storage medium of claim 12 , wherein determining the subset of associated users comprises:

determining content items on the content sharing server with an interaction by the user;

for each content item viewed by the user, determining other users of the set of associated users that had an interaction with the content item to determine an affinity score for each user; and

selecting users for the subset of users with an affinity score that exceeds a threshold.

15. The non-transitory machine-readable storage medium of claim 12 , wherein the social relationship data is determined from an address book of the user.

16. The non-transitory machine-readable storage medium of claim 12 , wherein the operations further comprise generating a subscription to the selected users on the content sharing server.

17. The non-transitory machine-readable storage medium of claim 12 , wherein the user is also a member of an online social network separate from the content sharing server, and wherein the social relationship data is determined based on connections of the user on the social network to other users of the social network.

18. A system comprising:

a memory to store a plurality of content items;

a processing device coupled to the memory, the processing device to:

identify social relationship data for a user, the social relationship data comprising a set of associated users;

determine a subset of the set of associated users based on similarity of content item interaction on a content sharing server;

provide the subset of associated users as recommended users to follow by the user;

receive an indication of a selection of users from the subset of associated users;

originate a social content item recommendation list for the user based on the selected users; and

provide the social content item recommendation list to the user.

19. The system of claim 18 , wherein the subset of associated users is determined based on at least one of current subscriptions of the user or an activity history of the user on the content sharing server.

20. The system of claim 18 , wherein to determine the subset of associated users, the processing device is to:

determine content items on the content sharing server with an interaction by the user;

for each content item viewed by the user, determine other users of the set of associated users that had an interaction with the content item to determine an affinity score for each user; and

select users for the subset of users with an affinity score that exceeds a threshold.

21. The system of claim 18 , wherein the user is also a member of an online social network separate from the content sharing server, and wherein the social relationship data is determined based on connections of the user on the social network to other users of the social network.

22. The system of claim 18 , wherein the social relationship data is determined from an address book of the user.

23. The system of claim 18 , wherein the processing device is further to generate a subscription to the selected users on the content sharing server.

24. A system comprising:

a memory to store a plurality of content items;

a processing device coupled to the memory, the processing device to:

identify social relationship data for a user, the social relationship data comprising a set of associated users;

determine a subset of the set of associated users based on similarity of content item interaction on a content sharing server;

use content items associated with the subset of associated users to originate a social content item recommendation list for the user; and

provide the social content item recommendation list to the user.

25. The system of claim 24 , wherein the subset of associated users is determined based on at least one of current subscriptions of the user or an activity history of the user on the content sharing server.

26. The system of claim 24 , wherein, to determine the subset of associated users, the processing device is to:

determine content items on the content sharing server with an interaction by the user;

for each content item viewed by the user, determine other users of the set of associated users that had an interaction with the content item to determine an affinity score for each user; and

select users for the subset of users with an affinity score that exceeds a threshold.

27. The system of claim 24 , wherein the user is also a member of an online social network separate from the content sharing server, and wherein the social relationship data is determined based on connections of the user on the social network to other users of the social network.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 30, 2026
From: GOOGLE LLC
To: BLACKBERRY LIMITED
Reel/Frame 075465/0538 →
CHANGE OF NAME Recorded Dec 5, 2017
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 044695/0115 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 31, 2014
From: LEWIS, JUSTIN; LEE-CHAN, JEFFREY
To: GOOGLE INC.
Reel/Frame 032566/0261 →