Methods, systems and devices for monitoring and controlling media content using machine learning
Aspects of the subject disclosure may include, for example, embodiments that comprise provisioning a target user profile and obtaining viewing history data. Further embodiments include generating a group of control rules according to the target user profile and training a machine learning application according to the viewing history data and the group of control rules. Additional embodiments include receiving a first indication that a first media content is to be presented to a target user. Also, embodiments include determining by the machine learning application, that the first media content does not conform to the group of control rules and providing a first notification that the first media content does not conform to the group of control rules. Other embodiments are disclosed.
1. A device, 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:
determining, by a machine learning application, that a first media content presented to a target user in a primary window on a display of a target user device does not conform to a group of control rules;
providing a selectable list of distraction media content to the target user device, wherein the selectable list of distraction media content is presented in a distraction window on the display while the first media content is being presented in the primary window; and
providing a selected distraction media content to the target user device in response to receiving a first user-generated input, wherein the first user-generated input comprises a selection of the selected distraction media content, wherein the selectable list of distraction media content comprises the selected distraction media content, wherein the selected distraction media content is presented in the primary window.
2. The device of claim 1 , wherein the operations comprise:
obtaining viewing history data; and
training the machine learning application according to the viewing history data and the group of control rules.
3. The device of claim 1 , wherein the operations comprise providing a first notification to a communication device associated with a monitoring user.
4. The device of claim 1 , wherein the providing of the distraction media content is in response to determining the first media content to be presented to the target user is passive media content.
5. The device of claim 1 , wherein the operations comprise generating the group of control rules.
6. The device of claim 1 , wherein the operations comprise retraining the machine learning application according to the first media content not conforming to the group of control rules.
7. The device of claim 1 , wherein the operations comprise:
obtaining the first media content; and
analyzing audio content of the first media content using speech recognition resulting in audio content analysis, wherein the determining, by the machine learning application, of the first media content does not conform to the group of control rules comprises determining, by the machine learning application, the first media content does not conform to the group of control rules according to the audio content analysis.
8. The device of claim 1 , wherein the operations comprise:
obtaining the first media content; and
analyzing image content of the first media content using image recognition resulting in image content analysis, wherein determining, by the machine learning application, the first media content does not conform to the group of control rules comprises determining, by the machine learning application, the first media content does not conform to the group of control rules according to the image content analysis.
9. The device of claim 2 , wherein the operations comprise accessing rating information, wherein training the machine learning application comprises training the machine learning application according to the rating information.
10. The device of claim 2 , wherein the operations comprise receiving a second user-generated input, wherein the second user-generated input comprises a list of exemplary media content, wherein the training the machine learning application comprises training the machine learning application according to the list of exemplary media content.
11. The device of claim 3 , wherein the operations comprise transmitting the first media content to the communication device associated with the monitoring user, wherein the first media content is presented on the communication device associated with the monitoring user.
12. The device of claim 3 , wherein the operations comprise preventing presentation of the first media content in response to receiving a second user-generated input from the communication device associated with the monitoring user indicating prevention of presentation of the first media content.
13. The device of claim 5 , wherein the operations comprise receiving crowd source input, wherein generating the group of control rules comprises generating the group of control rules according to the crowd source input.
14. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, comprising:
obtaining a first media content;
analyzing audio content of the first media content using speech recognition resulting in audio content analysis;
determining, by a machine learning application, that the first media content presented to a target user in a primary window on a display of a target user device does not conform to a group of control rules according to the audio content analysis;
providing a selectable list of distraction media content to the target user device, wherein the selectable list of distraction media content is presented in a distraction window on the display while the first media content is being presented in the primary window; and
providing a selected distraction media content to the target user device in response to receiving a first user-generated input, wherein the first user-generated input comprises a selection of the selected distraction media content, wherein the selectable list of distraction media content comprises the selected distraction media content, wherein the selected distraction media content is presented in the primary window.
15. The non-transitory machine-readable storage medium of claim 14 , wherein the operations comprise:
obtaining viewing history data; and
training the machine learning application according to the viewing history data and the group of control rules.
16. The non-transitory machine-readable storage medium of claim 15 , wherein the operations comprise accessing rating information, wherein training the machine learning application comprises training the machine learning application according to the rating information.
17. The non-transitory machine-readable storage medium of claim 15 , wherein the operations comprise receiving a second user-generated input, wherein the second user-generated input comprises a list of exemplary media content, wherein the training the machine learning application comprises training the machine learning application according to the list of exemplary media content.
18. A method, comprising:
obtaining, by a processing system including a processor, a first media content;
analyzing, by the processing system, image content of the first media content using image recognition resulting in image content analysis;
determining, by the processing system, by a machine learning application, that the first media content presented to a target user in a primary window on a display of a target user device does not conform to a group of control rules according to the image content analysis;
providing, by the processing system, a selectable list of distraction media content to the target user device, wherein the selectable list of distraction media content is presented in a distraction window on the display while the first media content is being presented in the primary window; and
providing, by the processing system, a selected distraction media content to the target user device in response to receiving a first user-generated input, wherein the first user-generated input comprises a selection of the selected distraction media content, wherein the selectable list of distraction media content comprises the selected distraction media content, wherein the selected distraction media content is presented in the primary window.
19. The method of claim 18 , comprising generating, by the processing system, the group of control rules.
20. The method of claim 19 , comprising receiving, by the processing system, crowd source input, wherein generating the group of control rules comprises generating, by the processing system, the group of control rules according to the crowd source input.