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.

A content segmentation system includes a computing platform having processing hardware and a system memory storing a software code and a trained machine learning model. The processing hardware is configured to execute the software code to receive content, the content including multiple sections each having multiple content blocks in sequence, to select one of the sections for segmentation, and to identify, for each of the content blocks of the selected section, at least one respective representative unit of content. The software code is further executed to generate, using the at least one respective representative unit of content, a respective embedding vector for each of the content blocks of the selected section to provide a multiple embedding vectors, and to predict, using the trained machine learning model and the embedding vectors, subsections of the selected section, at least some of the subsections including more than one of the content blocks.

Systems, methods and articles of manufacture for are provided for analyzing user behavior in real time by ingesting telemetry data related to a streaming media application; feeding the telemetry data to a machine learning model (MLM) that produces a User Experience (UX) command based on the telemetry data and prior telemetry data received from the content streaming application; selecting content items to provide to the client device based on the telemetry data; determining, based on the telemetry data, whether the client device has sufficient free resources to receive the UX command and the content items in a current time window while providing a predefined level of service; when client device has sufficient free resources to receive the UX command and the content items, encapsulating the UX command with the content items in a content stream; and transmitting the content stream to the client device.

Methods, systems, and computer media provide for identifying exclusion zones in frames of a video, aggregating those exclusion zones for a specified duration or number of frames, defining a inclusion zone within which overlaid content is eligible for inclusion, and providing overlaid content for inclusion in the inclusion zone. The exclusion zones can include regions in which significant features are detected such as text, human features, objects from a selected set of object categories, or moving objects.

A viewing abandonment factor estimation device includes a memory; and a processor configured to include an estimation model for estimating a factor, the estimation model including a plurality of feature quantities measurable for viewing of a video relevant to an adaptive bit rate video distribution as inputs and the factor of the viewing abandonment in the viewing as an output.

Methods, apparatus, systems and articles of manufacture are disclosed for determining the demographics of users. An example apparatus includes at least one memory, instructions, and processor circuitry to at least one of execute or instantiate the instructions to extract a first media data pair from first media presentation data from a media provider, identify a second media data pair in second media presentation data based on a comparison of the first media data pair and the second media presentation data, the second media data pair generated in response to a meter accessing streaming data associated with a second media presentation device accessing the streaming media, identify a panelist associated with the second media data pair, and, in response to identifying the panelist, cause a server to associate the second media data pair and demographic data associated with the panelist included in a report by transmitting the report to the server.

A method of assigning advertisements to slots in video channels of a bundle of channels provided to an end user. The method includes managing credits, for each specific channel of the channels, indicative of a difference between a number of advertisements provided by an owner of the specific channel that were displayed on other channels and a number of advertisements provided by owners of other channels displayed on the specific channel In addition, scores indicative of a predicted success of the advertisement with the end user are calculated for a plurality of advertisements. An advertisement to be displayed to the end user is selected responsive to a function of both the calculated scores and the managed credits.

Embodiments are disclosed for determining an answer to a query associated with a graphical representation of data. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including an unprocessed audio sequence and a request to perform an audio signal processing effect on the unprocessed audio sequence. The one or more embodiments further include analyzing, by a deep encoder, the unprocessed audio sequence to determine parameters for processing the unprocessed audio sequence. The one or more embodiments further include sending the unprocessed audio sequence and the parameters to one or more audio signal processing effects plugins to perform the requested audio signal processing effect using the parameters and outputting a processed audio sequence after processing of the unprocessed audio sequence using the parameters of the one or more audio signal processing effects plugins.

Systems and methods for organizing and controlling the display of content, then measuring the effectiveness of that content in modifying behavior, within a particular temporal and special dimension, so as to minimize or eliminate confounding effects.