Methods, apparatus, systems and articles of manufacture to assign viewers to media meter data are disclosed. An apparatus includes processor circuitry to execute computer readable instructions to at least: identify a candidate household from a plurality of second households to associate with a first household based on an analysis of a first duration of time first media was presented by a first media presentation device and a second duration of time second media was presented by second media presentation devices; match different ones of first panelists of the first household with matching ones of second panelists of the candidate household; and impute respective portions of the first duration of time to the different ones of the first panelists based on portions of the second duration of time for which the matching ones of the second panelists of the candidate household were exposed to the second media.

The present invention may include a computer receives multimedia data. The computer parses the multimedia data into an audio stream. The computer analyzes the audio stream to identify recognized patterns. The computer calculates a probability of an undesired content based on the recognized patterns and taking an action based on determining the probability is above a threshold.

A system and method for making program recommendations to users of a network-based video recording system utilizes expressed preferences as inputs to collaborative filtering and Bayesian predictive algorithms to rate television programs using a graphical rating system. The predictive algorithms are adaptive, improving in accuracy as more programs are rated.

An example apparatus includes processor circuitry to: access first input data from meters, the meters to monitor media devices associated with a plurality of panelists, the first input data including media source data and panel data; reduce a dimensionality of the first input data to generate second input data of reduced dimensionality relative to the first input data, the dimensionality of the first input data to be reduced based on a prior probability of an audience rating associated with the plurality of panelists and an approximation of a dependency of the audience rating on at least one of the media source data and the panel data; and decode the second input data of reduced dimensionality to output a probability model parameter for a multivariate probability model, the multivariate probability model having dimensions corresponding to the first input data, the multivariate probability model to label census data.

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, systems, and computer readable media may be operable to facilitate anticipatory conditioning of multimedia content for delivery to one or more devices. A multimedia device may track and record correlations between each of a plurality of devices, wherein the correlations are based on the order in which one or more devices request synchronization of a piece of content following a request by a first device for synchronization of the same piece of content. The multimedia device may update device correlations with each subsequent content synchronization request. When the multimedia device receives a synchronization request for a piece of content, the multimedia device may identify a device correlated with the requesting device and may initiate a conditioning of the piece of content for delivery to the correlated device without first receiving a request for synchronization of the piece of content from the correlated device.

Methods and systems are disclosed for using multiple reach optimization models together. These models may be used by an optimization system that helps an advertisement campaign manager decide how advertisements should be allocated between different media assets. In some embodiments, the models may be run simultaneously while their results and compared, and execution of some models may be ended based on the comparisons. In some embodiments, models may be combined together to create new models. In some embodiments, results from a first model may used as input in a second model running concurrently. In some embodiments, results from a previous execution of a model may be used to warm-start a subsequent execution of the model.

Methods, apparatus, systems and articles of manufacture are disclosed for a viewing condition probability calculator. The viewing condition probability calculator enumerates a list of all viewing combinations for a tuning event, for a number of people N at a location. A probability for each of the viewing combinations is determined, using an independent probability of viewing for each of the N people at the location. A probability of a viewing condition is determined using the probabilities of a first set of viewing combinations that have a first common characteristic.

Techniques are provided herein for generating and providing micro-previews of edited versions (e.g., a movie trailer) associated with media content. In accordance with at least one embodiment, a plurality of edited content (e.g., movie trailers) corresponding to a collection of motion pictures may be obtained, the collection of motion pictures being related by a collection category. A plurality of respective play durations for respective items of the plurality of edited content may be determined. A plurality of respective start times for the respective items of the plurality of edited content may be determined. At least a subset of the plurality of edited content may be played (e.g., consecutively) based at least in part on the plurality of respective start times and the plurality of respective play durations for the respective items of the collection of motion pictures.

Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.