Customized options for consumption of content
Systems and methods for consuming content. A computing device may receive data. The computing device may determine an inference. The computing device may manage content. The computing device may manage content based on the inference.
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;
determining, by the computing device based on the portion of the data, a predictive inference regarding a likelihood of consumption of a 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 , further comprising categorizing the data into categories of data comprising:
a first category of data suitable for inferring the likelihood of consumption of the 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 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 the 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;
provide a predictive inference regarding a likelihood of consumption of a specific media asset by the user at a future point in time, the predictive inference being based on the 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;
generating, based on the portion of the data, 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 , further comprising categorizing the data into categories of data comprising:
a first category of data suitable for inferring the likelihood of consumption of the 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 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.