Activity Based Recommendations within a Social Networking Environment Based Upon Graph Activation

• US 20140074893A1
• Filed: 01/15/2013
• Published: 03/13/2014
• Est. Priority Date: 09/13/2012
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Griffin, Keith
• Granted Patent: US 9,147,008 B2
• Time in Patent Office: Days
• US Class Current: 707/798
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

In a network environment between a group of endpoint computing devices, where content is shared between the group of endpoint computing devices via a social network platform, techniques are described herein for receiving a social activity feed associated with the social network platform, the social activity feed including activities occurring within the social network platform. An algorithm is applied to a social graph of a user at an endpoint computing device of the group to determine a prioritization of nodes within the user'"'"'s social graph, activities within the social activity feed are associated with nodes of the user'"'"'s social graph, and recommendations are provided to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph.

Claims

1. A method comprising:

in a network environment between a group of endpoint computing devices, wherein content is shared between the group of endpoint computing devices via a social network platform, receiving a social activity feed associated with the social network platform, the social activity feed comprising activities occurring within the social network platform;

applying an algorithm to a social graph of a user at an endpoint computing device of the group to determine a prioritization of nodes within the user'"'"'s social graph;

associating activities within the social activity feed with nodes of the user'"'"'s social graph; and

providing recommendations to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph.

2. The method of claim 1, wherein the applying the algorithm further comprises:

designating a source node within the social graph; and

prioritizing nodes within the social graph based upon a distance of nodes from the source node.

3. The method of claim 2, wherein a plurality of source nodes are designated within the social graph.

4. The method of claim 2, wherein the prioritizing nodes within the social graph further comprises:

applying an activation value to nodes within the social graph, based upon a decay factor, such that a first node has a greater activation value in relation to a second node that is further in distance from the source node in relation to the first node.

5. The method of claim 4, wherein the providing recommendations to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph further comprises:

eliminating each node and any corresponding activity within the social activity feed associated with each node from recommendation analysis based upon an activation value associated the node is less than a threshold value.

6. The method of claim 2, wherein the designating a source node within the social graph is based upon a first activity in which the user is currently engaged within the social network platform.

7. The method of claim 6, further comprising, in response to the user switching from a first activity to a second activity:

re-applying the algorithm to the social graph of the user to determine another prioritization of nodes within the user'"'"'s social graph, including designating a different source node based upon the re-applying of the algorithm and re-prioritizing nodes within the social graph based upon a distance of nodes from the different source node;

associating activities within the social activity feed with nodes of the user'"'"'s social graph; and

providing recommendations to the user of activities within the social activity feed that correspond with re-prioritized nodes of the user'"'"'s social graph.

8. The method of claim 1, further comprising:

providing different recommendations to different users of activities within the social activity feed that correspond with a prioritization of nodes for the social graph of each user.

9. An apparatus comprising:

a memory configured to store instructions including one or more applications that receive and store a social activity feed associated with a social network platform within a network environment between a group of endpoint computing devices, wherein content is shared between the group of endpoint computing devices via the social network platform, the social activity feed comprising activities occurring within the social network platform; and

a processor configured to execute and control operations of the one or more applications so as to;

apply an algorithm to a social graph of a user at an endpoint computing device of the group to determine a prioritization of nodes within the user'"'"'s social graph;

associate activities within the social activity feed with nodes of the user'"'"'s social graph; and

provide recommendations to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph.

10. The apparatus of claim 9, wherein the processor is further configured to apply the algorithm by:

designating a source node within the social graph; and

prioritizing nodes within the social graph based upon a distance of nodes from the source node.

11. The apparatus of claim 10, wherein the processor, via application of the algorithm, is further configured to designate a plurality of source nodes within the social graph.

12. The apparatus of claim 10, wherein the processor, via application of the algorithm, is further configured to prioritize nodes within the social graph by:

applying an activation value to nodes within the social graph, based upon a decay factor, such that a first node has a greater activation value in relation to a second node that is further in distance from the source node in relation to the first node.

13. The apparatus of claim 12, wherein the processor is further configured to provide recommendations to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph by:

eliminating each node and any corresponding activity within the social activity feed associated with each node from recommendation analysis based upon an activation value associated the node is less than a threshold value.

14. The apparatus of claim 10, wherein the processor, via application of the algorithm, is further configured to designate a source node within the social graph based upon a first activity in which the user is currently engaged within the social network platform.

15. The apparatus of claim 14, wherein the processor, via application of the algorithm and in response to the user switching from a first activity to a second activity, is further configured to:

re-apply the algorithm to the social graph of the user to determine another prioritization of nodes within the user'"'"'s social graph, including designating a different source node based upon the re-applying of the algorithm and re-prioritizing nodes within the social graph based upon a distance of nodes from the different source node;

associate activities within the social activity feed with nodes of the user'"'"'s social graph; and

provide recommendations to the user of activities within the social activity feed that correspond with re-prioritized nodes of the user'"'"'s social graph.

16. The apparatus of claim 9, wherein the processor, via application of the algorithm, is further configured to:

provide different recommendations to different users of activities within the social activity feed that correspond with a prioritization of nodes for the social graph of each user.

17. One or more computer readable storage media encoded with software comprising computer executable instructions and when the software is executed operable to:

in a network environment between a group of endpoint computing devices, wherein content is shared between the group of endpoint computing devices via a social network platform, receive a social activity feed associated with the social network platform, the social activity feed comprising activities occurring within the social network platform;

apply an algorithm to a social graph of a user at an endpoint computing device of the group to determine a prioritization of nodes within the user'"'"'s social graph;

associate activities within the social activity feed with nodes of the user'"'"'s social graph; and

provide recommendations to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph.

18. The computer readable storage media of claim 17, wherein the instructions are operable to apply the algorithm by:

designating a source node within the social graph; and

prioritizing nodes within the social graph based upon a distance of nodes from the source node.

19. The computer readable storage media of claim 18, wherein the instructions are operable to designate a plurality of source nodes within the social graph.

20. The computer readable storage media of claim 18, wherein the instructions are operable to prioritize nodes within the social graph by:

applying an activation value to nodes within the social graph, based upon a decay factor, such that a first node has a greater activation value in relation to a second node that is further in distance from the source node in relation to the first node.

21. The computer readable storage media of claim 20, wherein the instructions are operable to provide recommendations in real-time to the user of activities within the social activity feed that correspond with prioritized nodes of the user'"'"'s social graph by:

eliminating each node and any corresponding activity within the social activity feed associated with each node from recommendation analysis based upon an activation value associated the node is less than a threshold value.

22. The computer readable storage media of claim 18, wherein the instructions are operable to designate a source node within the social graph based upon a first activity in which the user is currently engaged within the social network platform.

23. The computer readable storage media of claim 22, wherein the instructions, in response to the user switching from a first activity to a second activity, are operable to:

re-apply the algorithm to the social graph of the user to determine another prioritization of nodes within the user'"'"'s social graph, including designating a different source node based upon the re-applying of the algorithm and re-prioritizing nodes within the social graph based upon a distance of nodes from the different source node;

associate activities within the social activity feed with nodes of the user'"'"'s social graph; and

provide recommendations to the user of activities within the social activity feed that correspond with re-prioritized nodes of the user'"'"'s social graph.

24. The computer readable storage media of claim 22, wherein the instructions are further operable to:

provide different recommendations to different users of activities within the social activity feed that correspond with a prioritization of nodes for the social graph of each user.