Customized options for consumption of content

• US 10,158,898 B2
• Filed: 07/26/2012
• Issued: 12/18/2018
• Est. Priority Date: 07/26/2012
• Status: Active Grant

• Current Assignee: TiVo Corporation (Adeia Inc.)
• Original Assignee: Comcast Cable Communications LLC (Comcast Corporation)
• Inventors: Harvey, John, Mattozzi, Michael, Hawthorne, Matthew, Volkman, Jeremy
• Primary Examiner(s): Nguyen, Tammy
• Application Number:
  US13/559,341
• Publication Number:
  US 20140032762A1
• Time in Patent Office: 2,336 Days
• Field of Search: 709226, 709221, 709220, 709205, 709206, 707748, 702104
• 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 21/44222 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 21/4826 using recommendation lists, e.g. of programs or channels sorted out according to their score

Abstract

Aspects of the disclosure relate to personalized options for consumption of content assets. In one aspect, the personalized options can be supplied (e.g., transmitted) asynchronously and can be indicative of information associated with a media asset of likely interest to an end user. In another aspect, the personalized options can permit administration of the content assets, such as automated generation of storage configuration(s) and/or playback configuration(s), based at least on consumption behavior of an end-user.

Claims

1. A method, comprising:

receiving, by a computing device, data indicative of current consumption of at least one of a plurality of media assets, wherein a portion of the data indicates an interaction by a user with the at least one of the plurality of media assets;

categorizing the data into categories of data comprising,

a first category of data suitable for inferring a likelihood of consumption of a specific media asset, and

a second category of data unsuitable for inferring the likelihood of consumption of the specific media asset,

wherein the portion of the data is categorized in the first category;

determining, by the computing device based on the portion of the data, a predictive inference regarding the likelihood of consumption of the specific media asset by the user at a future point in time; and

managing, by the computing device based on the predictive inference, prospective consumption of the specific media asset.

2. The method of claim 1, wherein the categorizing the data into the second category of data comprises:

determining that an interface coupled to a device for rendering the specific media asset is switched off for a specific time period; and

assigning a portion of the data received during the specific time period to the second category of data.

3. The method of claim 1, wherein the receiving, by the computing device, the data indicative of the current consumption of the at least one of the plurality of media assets comprises receiving data indicative of rendering of a linear-programming media asset.

4. The method of claim 3, wherein the managing, by the computing device based on the predictive inference, the prospective consumption of the specific media asset comprises providing a notification that the linear-programming media asset is available for consumption.

5. The method of claim 4, wherein the notification comprises a prompt to a user to consume the linear-programming media asset.

6. The method of claim 1, wherein the receiving, by the computing device, the data indicative of the current consumption of the at least one of the plurality of media assets comprises receiving data indicative of playback of a recorded media asset, and wherein the predictive inference indicates a likelihood of playback of the recorded media asset.

7. The method of claim 6, wherein the managing, by the computing device based on the predictive inference, the prospective consumption of the specific media asset comprises assigning, based on the predictive inference, a playback priority to the recorded media asset.

8. The method of claim 7, wherein the assigning, based on the predictive inference, the playback priority to the recorded media asset comprises providing a notification of the playback priority.

9. The method of claim 7, wherein the assigning, based on the predictive inference, the playback priority to the recorded media asset comprises configuring, based on the playback priority, a storage device that stores the recorded media asset.

10. The method of claim 6, wherein the managing, by the computing device based on the predictive inference, the prospective consumption of the specific media asset comprises assigning, based on the predictive inference, a deletion priority to the recorded media asset.

11. The method of claim 10, wherein the assigning, based on the predictive inference, the deletion priority to the recorded media asset comprises providing a notification of the deletion priority.

12. The method of claim 10, wherein the assigning, based on the predictive inference, the deletion priority to the recorded media asset comprises configuring, based on the deletion priority, a storage device that stores the recorded media asset.

13. An apparatus, comprising:

one or more processors; and

a memory storing processor executable instructions that, when executed by the one or more processors, cause the apparatus to;

receive data indicative of current consumption of at least one of a plurality of media assets, wherein a portion of the data indicates an interaction by a, user with the at least one of the plurality of media assets;

categorize the data into categories of data comprising,

a first category of data suitable for inferring a likelihood of consumption of a specific media asset, and

second category of data unsuitable for inferring the likelihood of consumption of the specific media asset,

wherein the portion of the data is categorized in the first category;

provide a predictive inference regarding the likelihood of consumption of the specific media asset by the user at a future point in time, the predictive inference being based on a portion of the data; and

manage, based on the predictive inference, prospective consumption of the specific media asset.

14. The apparatus of claim 13, wherein the processor executable instructions that, when executed by the one or more processors, further cause the apparatus to determine the predictive inference, wherein the predictive inference indicates a likelihood of playback of a recorded media asset.

15. The apparatus of claim 13, wherein the processor executable instructions that, when executed by the one or more processors, further cause the apparatus to receive the predictive inference.

16. The apparatus of claim 14, wherein the processor executable instructions that, when executed by the one or more processors, further cause the apparatus to assign, based on the predictive inference, a playback priority to the recorded media asset.

17. The apparatus of claim 14, wherein the processor executable instructions that, when executed by the one or more processors, further cause the apparatus to assign, based on the predictive inference, a deletion priority to the recorded media asset.

18. A method, comprising:

receiving, by a computing device, data indicative of current consumption of at least one of a plurality of media assets, wherein a portion of the data indicates an interaction by a user with the at least one of the plurality of media assets;

categorizing the data into categories of data comprising,

a first category of data suitable for inferring a likelihood of consumption of the plurality of media assets, wherein the first category of data indicates an interaction by a user with at least one of the plurality of media assets, and

a second category of data unsuitable for inferring the likelihood of consumption of the plurality of media assets;

generating, based on a portion of the data classified in the first category, a predictive inference regarding a likelihood of consumption of a specific media asset of the plurality of media assets by the user at a future point in time; and

managing, by the computing device based on the predictive inference, prospective consumption of the specific media asset.

19. The method of claim 18, wherein the categorizing the data into the second category of data comprises:

determining that an interface coupled to a device for rendering the specific media asset is switched off for a specific time period; and

assigning a portion of the data received during the specific time period to the second category of data.

20. The method of claim 18, wherein the receiving, by the computing device, the data indicative of the current consumption of the at least one of the plurality of media assets comprises receiving data indicative of rendering of a linear-programming media asset.