In one example, a method performed by a processing system including at least one processor includes obtaining a first stream of audio and video data, wherein the first stream of audio and video data comprises a lower-resolution version of a second stream of audio and video data that is transmitted to a first user device over a content distribution network and encrypted using a high-bandwidth digital content protection protocol, performing an analysis technique on the first stream of audio and video data in order to extract audio and video artifacts which from which content of the first stream of audio and video data is inferred, deriving a signature marker from the audio and video artifacts, and sending the signature marker to the first user device.

A method and system for controlling viewing of multimedia content includes collecting viewing control profiles and associated viewing control passwords via an Internet-protocol television portal, a web portal, and a mobile portal. The viewing control profile may be usable to restrict access to certain multimedia programs. The viewing control may be applied using a unified storefront application, providing access to multimedia content via the Internet-protocol television portal, the web portal, and the mobile portal, to offer and provide controlled access to the multimedia assets.

Systems and methods for virtual interactions are described. One or more users can view or listen to media, react to the media and share such media experience virtually with others. The media experience can take place synchronously, asynchronously or both.

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.

A system and method are disclosed for training a machine learning model using information pertaining to transmissions of one or more media items to user devices associated with a user account. Generating training data for the machine learning model includes generating first contextual information associated with a first user device and generating a first target output that identifies an indication of a preference of a user preference to cancel the first transmission. The method includes providing the training data to train the machine learning model.

Systems and methods are provided for generating a viewport for display. A user preference for a character and/or a genre of a scene in a spherical media content item is determined, wherein the spherical media content item comprises a plurality of tiles. A tile of the plurality of tiles is identified based on the determined user preference. A viewport to be generated for display at a computing device is predicted, based on the identified tile. A first tile to be transmitted to a computing device at a first resolution is identified, based on the predicted viewport to be generated for display. The tile is transmitted, to the computing device, at the first resolution.

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.

Methods, apparatus and systems related to production of a movie, a TV show or a multimedia content are described. In one example aspect, a system for producing a multimedia digital content includes a pre-production subsystem configured to receive information about a storyline, cameras, cast, and other assets for the content from a user. The pre-production subsystem is configured to generate one or more machine-readable scripts that include information about one or more advertisements. The system includes a production subsystem configured to receive the one or more machine-readable scripts from the pre-production system to obtain a footage according to the storyline. The production subsystem is further configured to embed one or markers corresponding to the one or more advertisements in the footage. The system also includes a post-production editing subsystem configured to detect the one or more markers embedded in the footage and replace each of the one or more markers with a corresponding advertising target.

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.

Methods and apparatus to calibrate media ratings based on return path data are disclosed. An apparatus includes a processor and memory including instructions that, when executed, cause the processor to: determine an initial rating for the media provided in a first geographic area based on return path data (RPD) tuning information obtained from RPD devices in subscriber households in the first geographic area; determine a first panelist rating for the media provided in a second geographic area based on first panel tuning information obtained from first metering devices in a first subset of panelist households in the second geographic area; determine a nonsubscriber calibration factor based on the first panelist rating; and determine a final rating for the media in the first geographic area by modifying the initial rating based on the nonsubscriber calibration factor.