Aspects of the subject disclosure may include, for example, receiving viewership data for a plurality of devices associated with a household, the devices for viewing content items received over a network from a network provider at the household, concatenating respective viewership data for respective devices of the plurality of devices, forming respective device documents, vectorizing the respective device documents to form vectorized device documents, concatenating the vectorized device documents to form a household corpus of viewership data for the household, training a clustering model on the household corpus of viewership data to form a household topological fingerprint (HTF) for the household, the HTF forming a vector classification of viewership patterns for the household, and selecting content items for the household based on the HTF. Other embodiments are disclosed.

An example method includes detecting an audience for a first item of media content being delivered to a user endpoint device, wherein the audience includes at least a first user, monitoring a reaction of the first user to the first item of media content during a presentation of the first item of media content on the user endpoint device, determining an adaptation to be made to the presentation of the first item of media content in response to the reaction of the first user, and sending an instruction to at least one device to make the adaptation to the presentation in response to the reaction of the first user.

Systems and associated methods are described for providing content recommendations. The system selects, using a multi-armed bandit solution model, a first plurality of content categories based on a reward score of each content category. The categories are displayed. When a user selects an item from the displayed categories, the system finds all categories that include the selected item, but rewards only the category with the highest score. The system selects, using the multi-armed bandit solution model, the second plurality of content categories based on the updated reward score of each content category. The categories are then displayed. The system may also repeat the steps to refine the multi-armed bandit solution model.

In some implementations, a user device can predictively route media content to a remote playback device based on playback context information obtained by the user device. The playback context can include local playback context information related to the state and/or context of the user device. The playback context can include remote playback context information related to the state and/or context of available remote playback devices. Based on the playback context information obtained by the user device, the user device can generate a predictive score for each available playback device that indicates or predicts the likelihood that the user will want to send media content to the corresponding playback device. The user device can generate and present a graphical user interface that can identify the playback devices having predictive scores over a threshold score. In some instances, the user device can automatically route selected media content to a predicted playback device.

Systems and methods are provided for providing an enhanced viewing experience for one or more users of an interactive media program. One example method includes receiving, at a computing device, the interactive media program, wherein the interactive media program comprises a plurality of alternative segments followed by a common segment. A selection of a first alternative segment is received and is generated for output. A summary of at least one segment from the plurality of alternative segments is generated, and the summary is generated for output. The common segment of the interactive media program is generated for output.

Systems and methods are described herein for recommending content restrictions to a user based on chatter in a social network of the user. The system analyzes chatter in the social network to identify a correlation between what is posted by users and the content that the users are posting about. The system stores a mapping between chatter and expected attributes of the content referenced by the chatter. The system will determine whether to block the content when an expected attribute is associated with a content restriction.

Systems and methods for generating and presenting content recommendations to new users during or immediately after the onboarding process, before any history of the new user's viewed content is available. A machine learning or other model may be trained to determine clusters of content genre values corresponding to genres of content watched by viewers. Clusters are thus associated with popular groupings of content genres viewed by many users. Clusters representing popular groupings of content genres may be selected for new users, and content corresponding to the selected clusters may be recommended to the new users as part of their onboarding process. A sufficient amount of content may be selected to fully populate any content recommendation portion of a new user onboarding page

A method includes obtaining a user focus indicator value that is associated with a subject. A plurality of filter values for a respective set of media content filters are determined based on the subject and contextual data. The method includes delivering, based on a first combination of the filter values, a first set of media content items associated with a first combination of content delivery mediums. The method includes delivering, based on a second combination of the filter values that is different from the first combination, a second set of media content items that is associated with a second combination of content delivery mediums that is different from the first combination of content delivery mediums. The second set is different from the first set.

Media content search results ranked by popularity is described. In embodiment(s), a search request for television media content can be initiated by a viewer, and television media content that is relevant to the search request can be identified. The relevant television media content can then be ranked based on a popularity rating and the relevant television media content can be displayed in an ordered list that is ordered by popularity rankings.

Systems and methods for detecting a conflict between viewing selections of two users before viewing a media asset. In some aspects, the method comprises receiving an audio input through an audio channel, detecting a first utterance from a first user and a second utterance from a second user in the input of the audio channel, parsing the first utterance and the second utterance, analyzing the first utterance and the second utterance to determine context about the first media asset and the second media asset, and presenting a conflict to the users to display on the media asset.