Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a first probability distribution indicative of actual durations of panel tuning segments, the panel tuning segments corresponding to time periods during which panelists were exposed to first media; generate a second probability distribution indicative of modelled durations of modelled tuning segments, the modelled tuning segments corresponding to modified lengths of the panel tuning segments; and estimate a set-on time for a media set associated with an RPD device based on RPD tuning information and the first and second probability distributions, the RPD tuning information reported from the RPD device, the RPD tuning information indicative of a reported RPD tuning segment during which the RPD device was accessing second media.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

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.

Methods and apparatus are disclosed for video transmission using tokens. According to one example, computer-readable storage media store instructions that cause a processor to: distribute, toward terminal devices of a plurality of viewers via a communication line, motion data or a first video including an animation of an avatar of a distributor generated on the basis of the motion data; distribute, toward the terminal devices of the plurality of viewer via the communication line, a second video related to a computer-implemented game generated on the basis of operation data by using a received web page; receive, via the communication line, token data indicating that any type of token among a plurality types of tokens is given to the distributor, the token data being generated by the terminal device of each viewer viewing the second video; calculate a score based on the total number of at least one type of tokens given to the distributor using the token data; and control a game object used in the game on the basis of the score.

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.

Devices, systems, and methods are provided for on-target rate optimization for video. A method may include receiving streaming video advertisement impression data; receiving user activity data indicative of day-parts when viewers watch content; generating, based on the streaming video advertisement impression data and the survey data, using a machine learning model, a demographic probability vector, wherein each entry of the demographic probability vector is indicative of a probability that a viewer is in a respective age range of the non-overlapping demographic groups; generating, using the machine learning model, an audience recognition model with the demographic probability vector; generating a synthetic audience model predicting future advertisement viewing behavior; generating an assignment of an advertisement bid to a respective demographic group of the non-overlapping demographic groups; and generating, based on the assignment, a list of target demographic groups of the non-overlapping demographic groups for a bid request associated with the advertisement bid.

A system includes a computing platform having processing hardware and a memory storing an asset library and software code including a recommendation engine. The processing hardware executes the software code to receive, from a user, group generation data and a preferences profile of the user, the group generation data identifying a group including the user and another user, and to send, to the other user, an invitation to join the group. The processing hardware also executes the software code to receive, from the other user, one of an acceptance or a refusal of the invitation, obtain, in response to receiving the acceptance, a preferences profile of the other user, generate, using the preferences profiles of the user and the other user, a group preferences profile for the group, and identify, using the recommendation engine and the group preferences profile, one or more assets in the asset library for the group.

A method of determining content effectiveness, predicting content engagement, and recommending actions related to content is carried out by a content management system. The content management and analysis system analyzes a piece of content submitted by a user, determines a desired outcome for the piece of content, determines an audience engagement for the piece of content, tracks an audience behavior for the piece of content, determines a target persona related to the piece of content, determines a likely intent of the target persona related to the piece of content, and assigns a value to the piece of content based on a content effectiveness determined from the desired outcome, the audience engagement, the audience behavior, and the target persona. A user interface can include a dashboard interface that displays one or more pieces of content and an effectiveness score for each of the one or more pieces of content.

Data on a user interacting with a media presentation is collected at a client device. The data includes facial image data of the user. The facial image data is analyzed to extract cognitive state content of the user. One or more emotional intensity metrics are generated. The metrics are based on the cognitive state content. The media presentation is manipulated, based on the emotional intensity metrics and the cognitive state content. An engagement score for the media presentation is provided. The engagement score is based on the emotional intensity metric. A facial expression metric and a cognitive state metric are generated for the user. The manipulating includes optimization of the previously viewed media presentation. The optimization changes various aspects of the media presentation, including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.

Example methods, apparatus, systems and articles of manufacture to determine synthetic total audience ratings are disclosed. Disclosed example apparatus are to access census data including census viewing statements associated with media content presented by census devices, access panel data including panelist viewing statements associated with media content presented by panel devices, the panel data including weights to represent numbers of individuals to be represented by corresponding panelists, divide the weights for respective ones of the panelists into respective sets of split weights, and assign the census viewing statements to at least subsets of the sets of split weights to determine the audience ratings for the population, the assignment of the census viewing statements to the at least subsets of the sets of split weights based on a reach constraint.