Automatic rating optimization

Patent metadata

Field	Value
Publication number	US-9456250-B2
Application number	US-201213621300-A
Country	US
Kind code	B2
Filing date	Sep 17, 2012
Priority date	Dec 15, 2006
Publication date	Sep 27, 2016
Grant date	Sep 27, 2016

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.

First claim

The invention claimed is:

1. A method, comprising:
receiving, by a content rating system, ratings that are associated with a content, wherein the ratings are received from rating sources, wherein a first one of the ratings is from a first one of the rating sources;
ascertaining, by the content rating system, an indication of whether the rating sources accessed the content;
determining, by the content rating system, an effect each of the ratings has on a popularity of the content for a time period after which the first one of the ratings is provided to at least one potential consumer of the content;
ascertaining by the content rating system, preference profiles, wherein each of the rating sources is associated with one of the preference profiles, wherein each of the preference profiles is based on consumption habits of the rating sources, wherein a first one of the preference profiles is associated with the first one of the rating sources and a second one of the preference profiles is associated with a potential consumer of the content;
determining, by the content rating system, a degree of relatedness between the first one of the preference profiles and the second one of the preference profiles;
detecting a number of times that the content was accessed by the first one of the rating sources; and
adjusting, by the content rating system, a weight of the first one of the ratings, wherein:
the weight of the first one of the ratings is increased if the first one of the ratings comprises a positive rating and the popularity of the content increases in the time period;
the weight of the first one of the ratings is increased if the first one of the ratings comprises a negative rating and the popularity of the content decreases in the time period;
the weight of the first one of the ratings is increased if the first one of the rating sources accessed the content;
the weight of the first one of the ratings is decreased if the first one of the ratings comprises a negative rating and the popularity of the content does not decrease in the time period;
the weight of the first one of the ratings is decreased if the first one of the ratings comprises a positive rating and the popularity of the content does not increase in the time period;
the weight of the first one of the ratings is decreased if the first one of the rating sources did not access the content;
the weight of the first one of the ratings is increased if the degree of relatedness comprises a high degree of relatedness;
the weight of the first one of the ratings is decreased if the degree of relatedness comprises a low degree of relatedness; and
the weight of the first one of the ratings is increased if the content was accessed on multiple occasions by the first one or the rating sources.

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, wherein the first one of the ratings is one of the 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 popularity of the content comprises
determining a number of times the content is accessed.

4. The method of claim 3 , wherein determining, by the content rating system, the popularity of the content further comprises determining a first rate of change, wherein the first rate of change is a rate of change of the number of times the content is accessed over a period of time.

5. The method of claim 4 , wherein determining, by the content rating system, the popularity of the content further comprises a second rate of change, wherein the second rate of change is a rate of change of the first rate of change.

6. The method of claim 1 , further comprising ascertaining an indication of a portion of the content that was accessed by the first one of the rating sources.

7. The method of claim 6 , wherein the adjusting further comprises:
increasing the weight of the first one of the ratings if the first one of the rating sources accessed the content in its entirety; and
decreasing the weight of the first one of the ratings if the first one of the rating sources did not access the content in its entirety.

8. The method of claim 1 , wherein the weight is an authority.

9. A content rating system, comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, comprising:
receiving ratings that are associated with a content, wherein the ratings are received from rating sources, wherein a first one of the ratings is from a first one of the rating sources;
ascertaining an indication of whether the rating sources accessed the content;
determining an effect each of the ratings has on popularity of the content for a time period after which the first one of the ratings is provided to at least one potential consumer of the content;
ascertaining preference profiles, wherein each of the rating sources is associated with one of the preference profiles, wherein each of the preference profiles is based on consumption habits of the rating sources, wherein a first one of the preference profiles is associated with the first one of the rating sources and a second one of the preference profiles is associated with a potential consumer of the content;
determining a degree of relatedness between the first one of the preference profiles and the second one of the preference profiles;
detecting a number of times that the content was accessed by the first one of the rating sources; and
adjusting a weight of the first one of the ratings, wherein:
the weight of the first one of the ratings is increased if the first one of the ratings if the first one of the ratings rating comprises a positive rating and the popularity of the content increases in the time period;
the weight of the first one of the ratings is increased if the first one of the ratings comprises a negative rating and the popularity of the content decreases in the time period;
the weight of the first one of the ratings is increased if the first one of the rating sources accessed the content;
the weight of the first one of the ratings is decreased if the first one of the ratings comprises a negative rating and the popularity of the content does not decrease in the time period;
the weight of the first one of the ratings is decreased if the first one of the ratings comprises a positive rating and the popularity of the content does not increase in the time period;
the weight of the first one of the ratings is decreased if the first one of the rating sources did not access the content;
the weight of the first one of the ratings is increased if the degree of relatedness comprises a high degree of relatedness;
the weight of the first one of the ratings is decreased if the degree of relatedness comprises a low degree of relatedness; and
the weight of the first one of the ratings is increased if the content was accessed on multiple occasions by the first one of the rating sources.

10. The content rating system of claim 9 , further configured to generate an average rating for the content, the average rating comprising at least two weighted ratings.

11. The content rating system of claim 10 , further configured to send the average rating to a content provider.

12. The content rating system of claim 9 , further configured to determine the popularity o

Assignees

• At & T Ip I Lp

Inventors

• Aaron Jeffrey
• Anschutz Thomas

Classifications

• H04N21/4532

  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 title

• H04N21/4668

  for recommending content, e.g. movies · CPC title

• H04N21/2407 Primary

  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 title

• H04N21/4667

  Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections · CPC title

• H04N21/4662

  characterized by learning algorithms · CPC title