Systems and methods are provided herein for displaying recommendations that are temporally relevant to activities of a user and are contextually relevant to a portion of viewed media. This may be accomplished by a media guidance application identifying activities a user has planned, as well as respective times for which each of the plurality of activities was planned to be performed by the user. The media guidance application may filter the activities by determining which of the first plurality of activities has a corresponding respective time that is within a threshold period of time. The media guidance application may then identify characteristics of each filtered activity and of a media asset that the user is consuming at the present moment, and may compute whether the characteristics match. If the characteristics match, the media guidance application may generate for display a recommendation relating to the respective activity.

Systems and methods are described to address shortcomings in conventional media systems via a novel technique to prevent corruption of a user's viewing profile. In some aspects, a user of an interactive media guidance application may select a media asset for viewing on a user device. The interactive media guidance application may receive a user viewing profile for the user from a remote server. If the media asset is determined to not be consistent with the user viewing profile, the interactive media guidance application may retrieve another user viewing profile for another user of the user device. If the media asset is determined to be consistent with the other user viewing profile, the interactive media guidance application may update the other user viewing profile based on the media asset.

A content recommendation method that includes: acquiring content cover images corresponding to multiple pieces of content accessed by a user account; acquiring cover image features of the multiple content cover images, and determining user account features of the user account according to the cover image features of the multiple content cover images; on the basis of cover image features of content to be recommended and the user account features, determining an access probability value of the user account accessing the content to be recommended; and providing, according to the access probability value, the content to be recommended to the user account.

Methods, apparatus, systems, storage media, etc., to perform media monitoring for mobile platforms using messaging associated with adaptive bitrate streaming are disclosed. An example media platform disclosed herein is to detect an adaptive bitrate streaming uniform resource locator (URL) in an outgoing message to be sent by the mobile platform to stream media in accordance with an adaptive bitrate streaming protocol, and associate the adaptive bitrate streaming URL with a time value. The disclosed example media platform is also to transmit the outgoing message to a first server to cause the media to be streamed to the mobile platform, and transmit the adaptive bitrate streaming URL and the time value to a second server different from the first server to cause a media impression associated with the mobile platform to be monitored.

This document describes, among other things, systems, methods, devices, and other techniques for using information about how long various videos were presented at client devices to determine subsequent video recommendations and search results. In some implementations, a computing can include a modeling apparatus, a front-end server, a request manager, one or more video file storage devices, a video selector, or a combination of some or all of these. The video selector can select video content for a particular digitized video among a plurality of digitized videos to serve to a computing device responsive to a request. The selection can be based at least in part on how long the particular digitized video has been presented at client devices associated with users having characteristics that match one or more characteristics of the user that submitted the request for video content, as indicated by the modeling apparatus.

Systems, methods, and computer-readable media for determining at least one valid mood for a collection of media content items of a media library are provided.

Disclosed is a display apparatus comprising: a display; a user input unit; and a processor configured to identify a user's viewing time based on a user's viewing history, create a list of content to be provided within the identified viewing time based on the viewing history and display the created content list on the display, and select at least one piece of content in the content list for viewing schedule based on a user input through the user input unit.

A method of identifying media content presented on a display device includes determining a selected input source providing a video signal to the display device, and then selecting a first set of content identification rules when it is determined that the selected input source is a first input source, and selecting a second set of content identification rules when it is determined that the selected input source is a second input source. The method further comprises applying the selected first set or second set of content identification rules to the video signal in order to generate content identification data for the media content presented on the display device. Application of the content identification rules includes waiting for a trigger event and applying an algorithm to one or more frames of the video signal following the trigger event.

A method of identifying media content presented on a display device includes determining a selected input source providing a video signal to the display device, and then selecting a first set of content identification rules when it is determined that the selected input source is a first input source, and selecting a second set of content identification rules when it is determined that the selected input source is a second input source. The method further comprises applying the selected first set or second set of content identification rules to the video signal in order to generate content identification data for the media content presented on the display device. Application of the content identification rules includes waiting for a trigger event and applying an algorithm to one or more frames of the video signal following the trigger event.

Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to perform probabilistic modeling for anonymized data integration and measurement of sparse and weakly-labeled datasets are disclosed. An apparatus includes a training controller to train a neural network to produce a trained neural network to output model parameters of a probability model, a model evaluator to execute the trained neural network on input data specifying a time of day, a media source, and at least one feature different from the time of day and the media source to determine one or more first model parameters of the probability model, and a ratings metric generator to evaluate the probability model based on input census data to determine a ratings metric corresponding to the time of day, the media source, and the at least one feature, the probability model configured with the one or more first model parameters.