GROUP-ASSOCIATED CONTENT RECOMMENDATION

• US 20120180107A1
• Filed: 01/07/2011
• Published: 07/12/2012
• Est. Priority Date: 01/07/2011
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Law, Stacey, Perez, Kathryn Stone, Clavin, John, Gammill, Kevin
• Application Number:
  US12/986,711
• Publication Number:
  US 20120180107A1
• Time in Patent Office: Days
• US Class Current: 726/3
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method of generating content recommendations to groups of users is provided. The method includes establishing a group, determining group-associated characteristics, where such characteristics include preferences independent of any merging, intersection or other combination of individual preferences of the group members, and providing content recommendations to the group based on the group-associated characteristics.

Claims

1. A method of generating content recommendations to groups of users, comprising:

establishing a group;

determining group-associated characteristics, where such characteristics include preferences independent of any merging, intersection or other combination of individual preferences of the group members; and

providing content recommendations to the group based on the group-associated characteristics.

2. The method of claim 1, where the group is established dynamically through observation of multi-person interactions.

3. The method of claim 1, where the group is established through collection assertion, verified through individual affirmation, or a desire to form a group.

4. The method of claim 1, where the characteristics are inferred dynamically in response to monitoring of group activity.

5. The method of claim 1, where the characteristics are determined in response to explicit inputs from the user.

6. The method of claim 1, where the characteristics are established through observations of online user activity.

7. The method of claim 6, where the characteristics are established as a result of determining that there is elevated interaction with respect to a particular topic or content item.

8. The method of claim 6, where the preferences are established in response to binary positive or negative inputs from mechanisms including tagging, social networks, blogging, voice recognition, and body posture.

9. The method of claim 1, further comprising:

determining the presence of individuals; and

in response to identifying the presence of individuals, authenticating and/or verifying identified users into a system.

10. A computing system for generating content recommendations, comprising:

a processor subsystem operatively coupled with a data-holding system which contains recommendation instructions executable by the processor subsystem to;

establish a group;

determine group-associated preferences, including preferences that are independent of any merging, intersection or other combination of individual preferences for digital content items; and

provide content recommendations to group members based on the group-associated preferences.

11. The computing system of claim 10, where the instructions are configured to dynamically establish the group based on observations of multi-person interactions.

12. The computing system of claim 10, where the instructions are configured to establish the group in response to collective desire, as affirmed through individual affirmation, to form a group.

13. The computing system of claim 10, where the instructions are operable to dynamically determine the group-associated preferences in response to observation of user consumption activity.

14. The computing system of claim 10, where the instructions are operable to determine the group-associated preferences in response to explicit user inputs relating to digital content items.

15. The computing system of claim 10, where the e instructions are operable to determine the group-associated preferences through monitoring of social network activity.

16. The computing system of claim 15, where the instructions are operable to establish a preference in response to elevated interaction relating to a digital content item, group of digital content items or topic.

17. The computing system of claim 15, where the instructions are operable to establish a preference in response to binary indications of preference or lack thereof in respect to a digital content item, group of digital content items or topic.

18. The computing system of claim 10, further comprising an authentication module configured to determine presence of users, and in response verify and/or authenticate present users into the system.

19. A method of generating content recommendations to groups of users, comprising:

establishing a group;

determining group-associated preferences, where such preferences include preferences independent of any merging, intersection or other combination of individual preferences of the group members;

determining the presence of the group in response to determining the presence of individual group members;

providing content recommendations to the group based on the group-associated preferences; and

tuning content recommendations over time as a result of increased intelligence achieved through monitoring of consumption activity of the group.

20. The method of claim 19, further comprising tuning content recommendations to the group in response to activity of group members in online social networks.