In some embodiments, a method receives a first set of probabilities mapping a behavior to a user for a set of behaviors in a video delivery system. A first part of a model is used to predict the first set of probabilities. The method receives a second set of probabilities mapping a user to a behavior for a set of users that are using an account on the video delivery system. A second part of the model is used to predict the second set of probabilities. A combined probability is calculated for the set of behaviors and the set of users based on the first set of probabilities and the second set of probabilities. The method updates a second parameter of the second part of the model while keeping a first parameter of the first part of the model fixed and outputs the second parameter of the second part of the model upon determining the training of the model is finished.

Developments in interactive programming guides that utilize a confluence of users/viewers from data that may be block chain and/or data collection from IoT and other devices, proximity sensing of viewership, and both machine and guided learning over a large dataset to produce rules for AI selection of content, format, and features presented to currently active or a nearby set of television users/viewers. Blockchain may be implemented separately for accounting, verification, billing, and/or fees/royalty payments owed to content owners/copyright holders. Playback may be initiated by a remote device and played on a same or yet another or a plurality of remote devices.

A method and apparatus for deep content tagging. A media device receives one or more first frames of a content item, where the one or more first frames spans a duration of a scene in the content item. The media device detects one or more objects or features in each of the first frames using a neural network model and identifies one or more first genres associated with the first frames based at least in part on the detected objects or features in each of the first frames. The media device further controls playback of the content item based at least in part on the identified first genres.

Aspects of the subject disclosure may include, for example, identifying content consumption data associated with media content consumption at a customer device, and generating a content selection recommendation for the customer device. Some embodiments can include determining a habit-based content selection vector for the customer device. Various embodiments can include determining the habit-based content selection vector based on a habit profile for the customer device. Some embodiments can include adjusting a content selection vector for the customer device based on the habit-based content selection vector for the customer device. Various embodiments can include generating the content selection recommendation for the customer device based on the adjusted content selection vector. Other embodiments are disclosed.

An example method includes receiving a selection of a media content, applying customized parental control rules associated with a user to the media content, providing a notification to apply a parental control associated with the customized parental control rules to the media content, receiving a confirmation to apply the parental control, and controlling the media content in accordance with the parental control that is applied.

Disclosed embodiments include a content consumption monitor (CCM) determines surges in content consumption based on changes in content consumptions scores. The CCM determines the content consumptions scores for domains and/or organizations (orgs) based on session events generated by different devices/users from the org and/or domain, a number of events generated by the org/domain, content and/or user interactions with the content indicated by the events, relevancy scores of the content to one or more topics, and/or other criteria. The CCM detects surges in consumption or interest in a topic for the domain/org when the consumption score reaches a threshold and/or within a period of time. The CCM may adjust the consumption score based on the changes in the relevancy, number of events and/or the number of users over different time periods. Other embodiments may be described and/or claimed.

An electronic device generates a respective user queue for each user of a plurality of users participating in a shared listening session. While providing a first media content item for playback, the device receives a second request, from a first user, to add a second media content item to the shared playback queue and updates the respective user queue for the first user. After receiving the second request, the electronic device receives a third request, from a second user, to add a third media content item to the shared playback queue and updates the respective user queue for the second user. The electronic device updates the shared playback queue using the respective user queues of the first user and the second user, including positioning the third media content item in an order of the shared playback queue to be played back before the second media content item.

Aspects of the subject disclosure may include, for example, applying first data associated with a first content item to a model to generate first classification characteristics, analyzing the first classification characteristics to generate a first marker, wherein the first marker delineates a first location of inventory within the first content item, selecting a first creative to populate a portion of the inventory, and populating, based on the selecting, the portion of the inventory with the first creative. Other embodiments are disclosed.

Techniques and mechanisms described herein facilitate providing dynamic digital object placement in a video stream. An exchange network for engagements within video streaming content is maintained, and a number of engagement entities and content providers are connected to the exchange network. An engagement proposal is received from an engagement entity in the exchange network, containing media assets for an engagement and proposed engagement information. Content provider requirements are also received from a content provider in the exchange network, containing content provider requirements and one or more engagement surfaces associated with a video stream. The exchange network determines that the received engagement proposal matches the received content provider requirements. Once the exchange network matches the two entities, the media assets from the engagement entity are dynamically inserted into the video stream published by the content provider by mapping the media assets to the one or more engagement surfaces.

Embodiments of the present disclosure provide methods, systems, and apparatuses for computing a channel incrementality ratio using a machine learning model.