An example to predict demographics for impressions includes a prediction manager to: determine that first demographic data corresponding to a first database proprietor subscriber does not match second demographic data corresponding to a media delivery device, both the first and second demographic data corresponding to an impression; obtain third demographic data corresponding to an Internet protocol address, the third demographic data obtained from a second database proprietor; and generate matched demographic data based on comparing the third demographic data to the first demographic data; and a modeler to generate a prediction model based on the matched demographic data, the prediction model to predict fourth demographic data for the impression.

Systems and methods are described herein for determining a level of user engagement based on user interactions. A media guidance application is configured to retrieve a first record of a first plurality of user inputs, including input type, received during consumption of a media asset. A second time interval, prior to the first time interval, is selected by shifting the first start time and the first end time. A second record of a second plurality of user inputs received during the second time interval, including input type, is retrieved. A first media asset consumed during the first time interval and a second media asset consumed during the second time interval are determined, and the level of user engagement for the first media asset is determined based on the first record and the second record.

Methods, apparatus, systems and articles of manufacture are disclosed. An example apparatus includes a controller to cause a people meter to emit a prompt for input of audience identification information at a first time and determine a first audience count based on the input, an audio detector to determine a second audience count based on signatures generated from audio data captured in the media environment, and a comparator to cause the people meter to not emit the prompt for at least a first time period after the first time when the first audience count is equal to the second audience count.

A method for distributing video content across a network, the method comprising: providing video data to a primary data source, associating control data with the video data, broadcasting the video data with associated control data from the primary data source to one or more user devices across the network, providing a media player on the respective user devices which is operable in response to reading the control data to create auxiliary data locally on the respective user devices while the media player is playing the video data, creating the auxiliary data locally on the respective user devices while the media player is playing the video data locally on the respective user devices. The control data defines one or more elements of the auxiliary data to be created by the media player including the elements of the auxiliary data which are to be retrieved from the primary data source and one or more secondary data sources.

Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

The present application provides a method of processing a video stream. The method includes: acquiring a plurality of video streams for a live-streaming event; determining respective feature information of the plurality of video streams; determining a feature information of a client in response to a video request message from the client; matching the respective feature information of the plurality of video streams with the feature information of the client respectively, so as to obtain respective matching degrees of the plurality of video streams with respect to the client; and selecting one video stream from the plurality of video streams to obtain a selected video stream according to the respective matching degrees of the plurality of video streams with respect to the client, and pushing the selected video stream to the client. The present application further provides a computer device, and a medium.

A display apparatus includes presence detection circuitry for detecting an individual in proximity to the display apparatus; a display for displaying video content and a user interface; a processor in communication with the user input circuitry, the display, and the search history database; and non-transitory computer readable media in communication with the processor that stores instruction code. The instruction code is executed by the processor and causes the processor to: a) determine, from the presence detection circuitry, a user in proximity of the display apparatus; b) determine one or more program types associated with the user; c) determine available programs that match the predicted one or more programs; and d) update the user interface to depict a listing of one or more of the available programs that match the predicted one or more programs.

Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.

Implementations claimed and described herein provide systems and methods for behavior assessment for an individual. In one implementation, user data for the individual is obtained from one or more digital sources. Categorized user data is created by transforming the user data into a platform independent format. The categorized user data is associated with a plurality of content-based bins. One or more behavioral insight categories are determined from the categorized user data. A plurality of behavioral metrics is determined based on the one or more behavioral insight categories and the categorized user data. A personality profile for the individual is generated by converting the plurality of behavioral metrics into one or more scores. A risk assessment for the individual is generated based on the personality profile.

Systems and methods for sorting favorite content sources are provided. A list of favorite content sources arranged in a first order is stored. The favorite content sources in the list are accessed according to the order of the favorite content sources in the list. At a given time, a user request to change a currently accessed content source to one of the favorite content sources in the list is received. In response to receiving the user request, an attribute of content presented on the currently accessed content source at the given time is identified. The favorite content sources in the list are rearranged into a second order based on the identified attribute. The favorite content sources in the list arc accessed according to the second order in response to receiving the user request.