METHOD AND APPARATUS FOR PROVIDING ENHANCED ELECTRONIC PROGRAM GUIDE WITH PERSONALIZED SELECTION OF BROADCAST CONTENT USING AFFINITIES DATA AND USER PREFERENCES

• US 20100287588A1
• Filed: 05/07/2010
• Published: 11/11/2010
• Est. Priority Date: 05/07/2009
• Status: Active Grant

• Current Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Original Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Inventors: Barton, Michael A., Cox, Stuart
• Granted Patent: US 8,490,136 B2
• Time in Patent Office: Days
• US Class Current: 725/40
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/26283 for associating distribution time parameters to content, e.g. to generate electronic program guide data
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• 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 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47 End-user applications
• CPC Class Codes: H04N 21/4755 for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/482 End-user interface for program selection broadcast systems using EPGs H04H60/72
• CPC Class Codes: H04N 21/4821 using a grid, e.g. sorted out by channel and broadcast time
• CPC Class Codes: H04N 21/4826 using recommendation lists, e.g. of programs or channels sorted out according to their score
• 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

An apparatus and method are provided to inform a user of a broadcast stream, which has multiple, concurrently received channels of program content, about recommendations of a subset of the content currently playing across the available channels or to be played within a selected future time period. The subset of content is selected based on user preferences and system data (e.g., program topic and channel affinities among the broadcast content and channels) to recommend a more diverse subset of content than would be discovered if only user preferences were employed to make the selection of recommended content.

Claims

1. A method of generating an enhanced electronic program guide (EPG) to a broadcast comprising programs playing concurrently on a plurality of received channels for display on a user device to facilitate perusal, navigation, and selection of programs for playback, the method comprising:

transmitting EPG data to the user device indicating programs playing on the channels for a selected period of time;

transmitting Affinities data to the user device, the Affinities data indicating at least one of relationships between the programs and relationships between the channels;

generating User Behavior data indicating user preferences for selection and playback of programs from among the channels of the broadcast; and

determining a subset of the programs playing on the channels that would be of interest to the user based on the Affinities data in combination with the User Behavior data.

2. A method as claimed in claim 1, wherein the Affinities data is determined by a content provider of the broadcast, and transmitting Affinities data comprises transmitting the same Affinities data to all user devices.

3. A method as claimed in claim 1, wherein the User Behavior data is generated automatically by the user device based on at least one of monitoring times when channels are selected for playback by a user via the user device, monitoring programs selected for playback by the user via the user device, storing data relating to user selection of favorite ones of the channels via the user device, storing data relating to user selection of a subset of the channels for assignment to corresponding preset buttons on the user device, storing data relating to a user request via the user device to suppress a selected one of the channels from playback, and storing data relating to a user request via the user device to suppress playback of a selected one of the programs.

4. A method as claimed in claim 1, wherein the Affinities data comprises a plurality of topics and identifications for each of the programs of at least one of the topics that corresponds to that program.

5. A method as claimed in claim 4, further comprising transmitting Topics Affinities data to the user device that indicates relationships between the topics.

6. A method as claimed in claim 5, wherein Topics Affinities data comprises values for the relationships that change depending on how much a user likes respective ones of the topics.

7. A method as claimed in claim 5, Wherein the Topics Affinities data comprises values for the relationships that change depending on how much a user dislikes respective ones of the topics.

8. A method as claimed in claim 5, wherein the Topics Affinities data comprises a matrix of weighted values comprising a list of the topics on an x-axis of the matrix and a list of the topics on a y-axis of the matrix to create a plurality of (x,y) coordinates being assigned a value selected from a range of values to indicate how much users, who generally like the topic identified as the x coordinate, will generally like the topic identified by the y coordinate.

9. A method as claimed in claim 1, wherein the Affinities data comprises Channel Affinities data comprising values for the relationships between the channels that change depending on how much a user likes respective ones of the channels.

10. A method as claimed in claim 1, wherein the Channel Affinities data comprises values for the relationships between the channels that change depending on how much a user dislikes respective ones of the channels.

11. A method as claimed in claim 1, wherein the Affinities data comprises a matrix of weighted values comprising a list of the channels on an x-axis of the matrix and a list of the channels on a y-axis of the matrix to create a plurality of (x,y) coordinates that are assigned a value selected from a range of values to indicate how much users, who generally like the channel identified as the x coordinate, will generally like the channel identified by the y coordinate.

12. A method as claimed in claim 1, wherein the determining a subset comprises determining Personal Affinities comprising

selecting a subset of the programs as recommendations;

assigning a weighting value to the topics corresponding to the recommended programs;

increasing the weighting value of any of the topics that have been elected by a user via the user device;

increasing the weighting value of any of the topics that correspond to programs played back and profiled according to the User Behaviors; and

generating a Personal Affinity List comprising topics having a selected weighting value that are different from the profiled topics and the elected topics.

13. A method as claimed in claim 12, wherein negative weighting values are assigned between two topics when a user of one of the topics generally dislikes the other of the two topics, and determining the Personal Affinities comprises changing the negative weighting values to positive weighting values for the topics that are any of elected and profiled.

14. A method as claimed in claim 12, further comprising:

prioritizing the recommended programs on the Personal Affinity List in accordance with the respective weighting values; and

displaying the prioritized list on the user device.