SYSTEMS AND METHODS FOR PRIORITIZING CONTENT BASED ON USER PROFILE RELEVANCE

• US 20130218906A1
• Filed: 03/18/2013
• Published: 08/22/2013
• Est. Priority Date: 03/31/2008
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Inventors: Frazier, Kristopher T.
• Granted Patent: US 9,143,579 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: G06F 16/437 Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/26258 for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list retrieval of multimedia data based on playlists G06F16/40
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• CPC Class Codes: H04N 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/47202 for requesting content on demand, e.g. video on demand

Abstract

In an exemplary method, at least one computing device 1) stores a plurality of content instances associated with a plurality of user profiles, 2) determines, based on a predefined relevance heuristic, a relevance between a user profile and each of the other user profiles included in the plurality of user profiles, 3) prioritizes, based on the determined relevance between the user profile and each of the other user profiles, the plurality of content instances relative to one another, and 4) provides, for display, data representative of the prioritized plurality of content instances.

Claims

1. A method comprising:

receiving, by at least one computing device from an access device, a request for a content instance included in a plurality of stored content instances associated with a plurality of user profiles, the request associated with a user profile included in the plurality of user profiles;

identifying, by the at least one computing device based on a predefined relationship heuristic, a plurality of other content instances included in the plurality of stored content instances as being related to the requested content instance, the plurality of other content instances associated with other user profiles included in the plurality of user profiles;

determining, by the at least one computing device based on a predefined relevance heuristic, a relevance between the user profile and each of the other user profiles;

prioritizing, by the at least one computing device based on the determined relevance between the user profile and each of the other user profiles, the other content instances relative to one another; and

providing, by the at least one computing device to the access device in response to the request, data representative of the requested content instance and the prioritized other content instances.

2. The method of claim 1, wherein the determining of the relevance between the user profile and each of the other user profiles comprises determining the relevance between the user profile and each of the other user profiles based at least in part on a measure of interaction between a user associated with the user profile and each other user associated with each of the other user profiles.

3. The method of claim 2, wherein the measure of interaction comprises at least one of:

a number of communications between the user associated with the user profile and each other user associated with each of the other user profiles;

a frequency of communications between the user associated with the user profile and each other user associated with each of the other user profiles; and

a ratio of overall communications between the user associated with the user profile and the other users associated with the other user profiles attributable to each of the other users.

4. The method of claim 1, wherein the determining of the relevance between the user profile and each of the other user profiles comprises determining a relevance between the user profile and each of the other user profiles based at least in part on a measure of reliance between a user associated with the user profile and each other user associated with each of the other user profiles.

5. The method of claim 4, wherein the measure of reliance comprises at least one of:

an indicator of common interests or experiences shared by the user associated with the user profile and each other user associated with each of the other user profiles;

a social status of each other user associated with each of the other user profiles;

an indicator of a past reliance of each other user associated with each of the other user profiles;

a relationship between the user associated with the user profile and each other user associated with each of the other user profiles; and

an inclusion of the user profile and one or more of the other user profiles in a common user group.

6. The method of claim 1, wherein the determining of the relevance between the user profile and each of the other user profiles comprises determining a relevance between the user profile and each of the other user profiles based at least in part on a measure of shared commonalities between the user profile and each of the other user profiles.

7. The method of claim 6, wherein the measure of shared commonalities comprises at least one of:

a number of relationships between one or more content instances associated with the user profile and one or more content instances associated with each of the other user profiles;

a number of relationships of a specific type between one or more content instances associated with the user profile and one or more content instances associated with each of the other user profiles;

a number of content instances that are common between the user profile and each of the other user profiles;

a number of content instances of a specific type that are common between the user profile and each of the other user profiles; and

a number of content instances associated with a specific topic that are common between the user profile and each of the other user profiles.

8. The method of claim 1, wherein the determining of the relevance between the user profile and each of the other user profiles comprises determining the relevance between the user profile and each of the other user profiles based at least in part on a weighted combination of an interaction factor, a reliance factor, and a commonality factor specified by the predefined relevance heuristic.

9. The method of claim 8, wherein:

the interaction factor includes a measure of interaction between a user associated with the user profile and each other user associated with each of the other user profiles;

the reliance factor includes a measure of reliance between the user associated with the user profile and each other user associated with each of the other user profiles; and

the commonality factor includes a measure of shared commonalities between the user profile and each of the other user profiles.

10. The method of claim 1, embodied as computer-executable instructions on at least one non-transitory computer-readable medium.

11. A method comprising:

storing, by at least one computing device, a plurality of content instances associated with a plurality of user profiles;

determining, by the at least one computing device based on a predefined relevance heuristic, a relevance between a user profile and each of the other user profiles included in the plurality of user profiles;

prioritizing, by the at least one computing device based on the determined relevance between the user profile and each of the other user profiles, the plurality of content instances relative to one another; and

providing, by the at least one computing device for display, data representative of the prioritized plurality of content instances.

12. The method of claim 11, wherein the determining of the relevance between the user profile and each of the other user profiles is based at least in part on a measure of interaction between a user associated with the user profile and each other user associated with each of the other user profiles.

13. The method of claim 12, wherein the measure of interaction comprises at least one of:

a number of communications between the user associated with the user profile and each other user associated with each of the other user profiles;

a frequency of communications between the user associated with the user profile and each other user associated with each of the other user profiles; and

a ratio of overall communications between the user associated with the user profile and the other users associated with the other user profiles attributable to each of the other users.

14. The method of claim 11, wherein the determining of the relevance between the user profile and each of the other user profiles is based at least in part on a measure of reliance between a user associated with the user profile and each other user associated with each of the other user profiles.

15. The method of claim 14, wherein the measure of reliance comprises at least one of:

an indicator of common interests or experiences shared by the user associated with the user profile and each other user associated with each of the other user profiles;

a social status of each other user associated with each of the other user profiles;

an indicator of a past reliance of each other user associated with each of the other user profiles;

a relationship between the user associated with the user profile and each other user associated with each of the other user profiles; and

an inclusion of the user profile and one or more of the other user profiles in a common user group.

16. The method of claim 11, wherein the determining of the relevance between the user profile and each of the other user profiles is based at least in part on a measure of shared commonalities between the user profile and each of the other user profiles.

17. The method of claim 16, wherein the measure of shared commonalities comprises at least one of:

a number of relationships between one or more content instances associated with the user profile and one or more content instances associated with each of the other user profiles;

a number of relationships of a specific type between one or more content instances associated with the user profile and one or more content instances associated with each of the other user profiles;

a number of content instances that are common between the user profile and each of the other user profiles;

a number of content instances of a specific type that are common between the user profile and each of the other user profiles; and

a number of content instances associated with a specific topic that are common between the user profile and each of the other user profiles.

18. The method of claim 11, wherein the determining of the relevance between the user profile and each of the other user profiles is based on a combination of:

a measure of interaction between a user associated with the user profile and each other user associated with each of the other user profiles;

a measure of reliance between the user associated with the user profile and each other user associated with each of the other user profiles; and

a measure of shared commonalities between the user profile and each of the other user profiles.

19. The method of claim 11, wherein said predefined relevance heuristic comprises at least one custom relevance condition defined by a user associated with the user profile.

20. The method of claim 11, embodied as computer-executable instructions on at least one non-transitory computer-readable medium.

21. A system comprising:

at least one computing device configured to;

store a plurality of content instances associated with a plurality of user profiles;

determine, based on a predefined relevance heuristic, a relevance between a user profile and each of the other user profiles included in the plurality of user profiles;

prioritize, based on the determined relevance between the user profile and each of the other user profiles, the plurality of content instances relative to one another; and

provide, for display, data representative of the prioritized plurality of content instances.