Automatic Rating Optimization

• US 20140081991A1
• Filed: 09/17/2012
• Published: 03/20/2014
• Est. Priority Date: 12/15/2006
• Status: Active Grant

• Current Assignee: Jeffrey Aaron, Thomas Anschutz
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Aaron, Jeffrey, Anschutz, Thomas
• Granted Patent: US 9,456,250 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: H04H 60/33 Arrangements for monitoring the users' behaviour or opinions
• CPC Class Codes: H04H 60/46 for recognising users' preferences
• CPC Class Codes: H04N 21/2407 Monitoring of transmitted content, e.g. distribution time, number of downloads arrangements for monitoring programmes for broadcast or for distribution combined with broadcast H04H20/14
• 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 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; 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 21/4662 characterized by learning algorithms
• 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 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4756 for rating content, e.g. scoring a recommended movie
• CPC Class Codes: H04N 21/6547 comprising parameters, e.g. for client setup
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38

Abstract

Automatic rating optimization is described. In an embodiment, ratings of a program can be received from one or more rating sources. Based on these ratings, a representation of a content selection mechanism can be sent to potential consumers of the content. Access events for the content can be counted over a duration of time so a determination can be made regarding how the ratings provided by each of the rating sources affect popularity of the content. A weight accorded to ratings received from each of the rating sources can be adjusted based on the determination. Profiles can be established for consumers and/or rating sources.

Claims

1. A method, comprising:

receiving, by a content rating system, ratings that are associated with content, wherein the ratings are received from rating sources;

ascertaining, by the content rating system, whether the rating sources accessed the content for which the ratings were received;

determining, by the content rating system, an effect each of the ratings has on popularity of the content;

weighting, by the content rating system, at least one of the ratings, the weighting being based upon results of the determining and ascertaining steps, wherein;

the weight of the rating is increased if the rating comprises a positive rating and the popularity of the content increases;

the weight of the rating is increased if the rating comprises a negative rating and the popularity of the content decreases; and

the weight of the rating is increased if the rating source accessed the content;

the weight of the rating is decreased if the rating is a negative rating and the popularity of the content does not decrease;

the weight of the rating is decreased if the rating comprises a positive rating and the popularity of the content does not increase; and

the weight of the rating is decreased if the rating source did not access the content;

associating, by the content rating system, the rating sources with preference profiles based on consumption habits of the rating sources; and

determining, by the content rating system, a degree of relatedness between a preference profile associated with the rating and preference profiles of each of the rating sources, wherein the weighting of the rating is further based upon a degree of relatedness between the preference profile associated with the rating and the preference profiles associated with the rating sources, and wherein the weighting comprises increasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a high degree of relatedness and the weighting comprises decreasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a low degree of relatedness.

2. The method of claim 1, further comprising:

generating, by the content rating system, an average rating for the content, the average rating comprising at least two weighted ratings; and

providing, by the content rating system, the average rating to a rating distribution system configured to provide the average rating to potential consumers of the content.

3. The method of claim 1, wherein determining, by the content rating system, the effect each of the ratings has on popularity of the content;

comprises;

analyzing, for each rating, data indicating a number of times the content is accessed after each of the ratings is received by the content rating system;

evaluating a speed of change in the popularity of the content over a duration of time; and

evaluating an acceleration of the change in the popularity of the content over the duration of time.

4. The method of claim 3, wherein the evaluated speed of change is a first evaluated speed of change over a first duration of time, the evaluated acceleration of change is a first acceleration of change over the first duration of time, and determining the effect each of the ratings has on popularity of the content further comprises:

evaluating a second speed of change in the popularity of the content over a second duration of time; and

evaluating a second acceleration of the change in the popularity of the content over the second duration of time.

5. The method of claim 1, wherein determining, by the content rating system, the effect each of the ratings has on popularity of the content includes periodically calculating a speed of popularity change and an acceleration of the popularity change for the content.

6. The method of claim 1, further comprising monitoring the content to determine what portion of the content was accessed by the rating sources.

7. The method of claim 6, wherein the weighting further comprises:

increasing the weight of the rating if the rating sources accessed the content in its entirety; and

decreasing the weight of the rating if the rating sources did not access the content in its entirety.

8. The method of claim 1, further comprising:

detecting whether the content was accessed on multiple occasions by a rating source; and

adjusting the weight of the rating based upon whether the content was accessed on multiple occasions by the rating source.

9. A tangible, non-transitory computer system, comprising:

a rating collection and distribution service configured to receive ratings of content from rating sources;

a rating adjusting service configured to;

ascertain whether the rating sources accessed the content for which the ratings were received;

determine how the ratings provided by each of the rating sources affect popularity of the content;

adjust a weight accorded to at least one of the ratings received from the rating sources based on the determining and ascertaining, wherein adjusting the weight comprises;

increasing the weight accorded to the rating if the rating comprises a positive rating and the popularity of the content increases;

increasing the weight accorded to the rating if the rating comprises a negative rating and the popularity of the content decreases;

decreasing the weight accorded to the rating if the rating comprises a negative rating and the popularity of the content does not decrease;

decreasing the weight accorded to the rating if the rating comprises a positive rating and the popularity of the content does not increase; and

decreasing the weight accorded to the rating if the rating sources did not access the content; and

wherein the rating adjusting service is further configured to associate the rating sources with preference profiles based on consumption habits of the rating sources and determine a degree of relatedness between a preference profile associated with the rating and preference profiles of each of the rating sources, wherein the weighting of the rating is further based upon a degree of relatedness between the preference profile associated with the rating and the preference profiles associated with the rating sources, and wherein the weighting comprises increasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a high degree of relatedness and the weighting comprises decreasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a low degree of relatedness.

10. The tangible, non-transitory computer system of claim 9, wherein the rating adjusting service is further configured to generate an average rating for the content, the average rating comprising at least two weighted ratings.

11. The tangible, non-transitory computer system of claim 10, wherein the rating collection and distribution service is further configured to provide the average rating to potential consumers.

12. The tangible, non-transitory computer system of claim 9, wherein the rating adjusting service is configured to determine how the ratings provided by each of the rating sources affect popularity of the content by:

counting access to the content over a duration of time;

evaluating a speed of change in the popularity of the content over the duration of time; and

evaluating an acceleration of the change in the popularity of the content over the duration of time.

13. The tangible, non-transitory computer system of claim 9, wherein the rating adjusting service is further configured to monitor the content to determine what portion of the content was accessed by the rating sources.

14. The tangible, non-transitory computer system of claim 13, wherein adjusting the weight further comprises:

increasing the weight of the rating if the rating sources accessed the content in its entirety; and

decreasing the weight of the rating if the rating sources did not access the content in its entirety.

15. The tangible, non-transitory computer system of claim 9, wherein the rating adjusting service is further configured to

detect whether the content was accessed on multiple occasions by the rating sources;

and

adjust the weight of the rating based upon whether the content was accessed on multiple occasions by the rating sources.

16. A method, comprising:

receiving, by a content rating system, ratings of content from rating sources;

detecting, by the content rating system, whether the rating sources accessed the content for which the ratings were received;

determining, by the content rating system, how the ratings provided by each of the rating sources affect popularity of the content;

weighting, by the content rating system, at least one of the ratings, the weighting being based upon results of the determining and ascertaining, wherein the weighting comprises;

increasing the weight of the rating if;

the rating comprises a positive rating and the popularity of the content increases;

or

the rating comprises a negative rating and the popularity of the content decreases; and

decreasing the weight of the rating if;

the rating comprises a negative rating and the popularity of the content does not decrease;

or

the rating comprises a positive rating and the popularity of the content does not increase;

associating the rating sources with preference profiles based on consumption habits of the rating sources; and

determining a degree of relatedness between a preference profile associated with the rating and preference profiles of each of the rating sources, wherein the weighting of the rating is further based upon a degree of relatedness between the preference profile associated with the rating and the preference profiles associated with the rating sources, and wherein the weighting comprises increasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a high degree of relatedness and the weighting comprises decreasing the weight of the rating if the preference profile of the rating and the preference profiles of the rating sources are determined to have a low degree of relatedness.

17. The method of claim 16, further comprising:

monitoring the content to determine what portion of the content was accessed by the rating sources, wherein the weighting further comprises;

increasing the weight of the rating if the rating sources accessed the content in its entirety; and

decreasing the weight of the rating if the rating sources did not access the content in its entirety.

18. The method of claim 16, further comprising:

detecting, by the content rating system, whether the content was accessed on multiple occasions by the rating sources; and

adjusting, by the content rating system, the weight of the rating based upon whether the content was accessed on multiple occasions by the rating sources.

19. The method of claim 16, further comprising generating an average rating for the content, the average rating comprising at least two weighted ratings, and providing the average rating to potential consumers.

20. The method of claim 16, wherein determining, by the content rating system, how the ratings provided by each of the rating sources affect popularity of the content comprises:

counting access to the content over a duration of time;

counting a speed of change in the popularity of the content over the duration of time; and

evaluating an acceleration of the change in the popularity of the content over the duration of time.