Systems and methods for searching, identifying, scoring, and providing access to companion media assets for a primary media asset are disclosed. In response to a request for companion content, metadata within a predefined time period of a play position when the request was made, is downloaded. A dynamic search template that contains search parameters based on the downloaded metadata is generated. In response to the search conducted using the search template, a plurality of companion media assets are identified and then verified. A trust score for the companion media asset is accessed. The trust score may be analyzed and modified based on its contextual relationship to the play position of the primary media asset. If the trust score is within a rating range, then a link to access the companion media asset, or a specific segment or play position within the companion media asset, is provided.

Systems and methods relate to display of insights, including a method including: causing a user display to display a graphical user interface (GUI) that enables a user to select a time range and a single digital display as a locale; and causing, based on the user selecting the time range and the single digital display as the locale, the user display to display, on the GUI, a list of a plurality of media content that have been displayed on the single digital display, each of the plurality of media content being ordered according to analysis insight for the single digital display selected and the time range selected. The analysis insight may include at least opportunity to see (OTS) counts of the plurality of media content on one or more digital displays associated with the locale.

This application describes methods, systems, and apparatus for allowing a user to easily determine whether the user and/or other user(s) have viewed content. For example, a program guide may display one or more graphics associated with the content (e.g., a movie poster), and in response to determining whether the user has viewed the content, the program guide may include an indication of whether the user has viewed the content. The program guide may include indications associated with multiple users (e.g., different colors, icons, graphics, or text). The program guide may filter the content based on whether the user has viewed the content (e.g., only display content the user has not viewed). A computing device storing the content may manage recording of the content based on whether the user has viewed the content (e.g., delete the recording if the user has viewed the content). A viewing history of the user may be maintained.

This disclosure includes systems and techniques that verify an educational quality of online videos, employing a platform that enables experts to endorse and/or recommend videos that are more readily accessible to end users. Certain aspects include a computing device for a service provider that receives a query from a user for video content. The computing device forwards the query to a hosting service, and in response to the query, the computing device receives, from the hosting service, a list of video content items it hosts. The computing device identifies, for each video content item within the list of video content items, an endorsement value associated with one or more experts. In some aspects, the computing device generates an aggregated list of video content items from a plurality of lists of video content items based on endorsement values. The computing device provides recommendations to the user using the endorsement values.

A display device comprising a memory in which a first application corresponding to a first content provision server and a second application corresponding to a second content provision server are stored; a display; and a processor to control, by executing the first application, the display to display a recommendation content list of content of the first content provision server based on a content use history of a user so that the content included in the recommended content list is aligned in a preset alignment. The preset alignment can be the same as an alignment of a recommendation content list of content of the second content provision server to be provided through the second application.

A method for recommending feed sources in an event feed includes generating an event feed comprising a plurality of feed items associated with a user. The event feed includes a recommendation feed item comprising one or more feed item sources not being followed by the user. The method further includes causing at least a portion of the event feed to be displayed to the user in the event feed. In accordance with a determination that the user is viewing a graphical user interface associated with a first software application, the recommendation feed item includes feed item sources associated with the first software application. In accordance with a determination that the user is viewing a graphical user interface associated with a second software application different from the first, the recommendation feed item includes feed item sources associated with the second software application.

Systems and methods are disclosed herein for a recommendations engine that generates content recommendations using a trained model that is personalized based on the information corresponding to content consumption. The disclosed techniques herein provide a trained model to provide content recommendations. The trained model may have been trained using a predefined set of training data agnostic of a particular user profile. A system receives information corresponding to content consumption. The system may associate the information corresponding to content consumption with a profile. The system generates a personalized model based on the information corresponding to content consumption and on the trained model. The personalized model may be associated with the user profile. The system generates the content recommendations using the personalized model. The system then causes to be provided the content recommendations.

Items of video content offered for viewing on a video-on-demand (VOD) platform of a digital TV service provider are each assigned a respective title and hierarchical address corresponding to hierarchically-arranged categories and subcategories within which the title for the video content is to be categorized. The title is listed in a location of an electronic program guide (EPG) using the same categories and subcategories as its hierarchical address. Any TV subscriber can access the EPG and navigate through its categories and subcategories to find a title for viewing on the TV. The EPG dynamically adjust its display listings of each level of categories, subcategories, and titles in order to minimize the number of remote control keypresses needed for a viewer to navigate to a title of interest. In one basic form, the EPG display is reordered by listing more frequently visited categories or subcategories first, and other less frequently visited categories or subcategories lower on the listing or out-of-sight on another page of the display.

The disclosed computer-implemented method may include accessing media segments that correspond to respective media items. At least one of the media segments may be divided into discrete video shots. The method may also include matching the discrete video shots in the media segments to corresponding video shots in the corresponding media items according to various matching factors. The method may further include generating a relative similarity score between the matched video shots in the media segments and the corresponding video shots in the media items, and training a machine learning model to automatically identify video shots in the media items according to the generated relative similarity score between matched video shots. Various other methods, systems, and computer-readable media are also disclosed.

Methods, systems, and apparatuses for user engagement analysis are described herein. An analytics subsystem may use a plurality of activity data to generate a plurality of user profiles, corresponding user interest clouds for each user device of a plurality of user devices, and a first interest cloud associated with a particular client identifier. The analytics subsystem may generate a second interest cloud associated based on a subset of a plurality of media assets associated with a threshold quantity of engagements. The analytics subsystem may determine a plurality of clusters of the plurality of media assets and may generate a content interest cloud for each of the plurality of clusters.