The Nielsen Comapny (us), LLC

The Nielson Company (us), LLC

Edward Murphy

Michael R Sheppard

Jonathan Lee Sullivan

Michael D Morgan

Ludo Daemen

Dongbo Cui

Balachander Shankar

Frank Downing

Molly Poppie

Jessica Lynn White

David Forteguerre

Chris Samuel Redino

Kelly Dixon

Francis C Fasinski

Diane Morovati Lopez

Jake Ryan Dailey

Jing Liu

Remy Spoentgen

Edmond Wong

PengFei Yi

Rachel Szabo

Beate Sissenich

Jennifer Carton

Robin J Gentry

Jacob Martin

Colin King

Emily Neuhoff

Katherine T Williams

Christopher Heider

Khaldoon Abu-Hakmeh

Dipti Umesh Shah

Matthew Zipoy

Olabode O Oyeneye

Methods, apparatus, systems, and articles of manufacture to perform computer-based monitoring of audiences of network-based media using information theory to estimate intermediate level unions are disclosed. An example apparatus to determine a deduplicated, census-based audience metric of media includes panel union calculator circuitry to calculate a threshold statistic corresponding to an intermediate union of a panel hierarchy, and census union calculator circuitry to calculate a deduplicated audience value corresponding to the intermediate union of the census hierarchy based on the threshold statistic.

Methods and apparatus to perform computer-based monitoring of audiences of network-based media by using information theory to estimate intermediate level unions

An example apparatus includes audience metrics collecting circuitry to access first audience metrics from a server, and access second audience metrics from the server, matrix building circuitry to build a matrix of the first audience metrics and the second audience metrics, missing values of the matrix corresponding to the second audience metrics, data transforming circuitry to transform the first audience metrics and the second audience metrics in the matrix, missing value calculating circuitry to determine imputed transformed values of the missing values using a recommender system, and the data transforming circuitry to recover imputed values of the missing values based on the imputed transformed values.

Methods and apparatus to generate audience metrics using matrix analysis

Methods, systems, apparatus, and articles of manufacture to determine causal effects are disclosed herein. An example apparatus includes a weighting engine to calculate a first set of weights corresponding to a first treatment dataset, a second set of weights corresponding to a second treatment dataset, and a third set of weights corresponding to a control dataset, the weighting engine to increase an operational efficiency of the apparatus by calculating the first set of weights, second set of weights, and third set of weights independently, a weighting response engine to calculate a first weighted response for the first treatment dataset, a second weighted response for the second treatment dataset, and determine a causal effect between the first treatment dataset and the second treatment dataset based on a difference between the first weighted response and the second weighted response, and a report generator to transmit a report to an audience measurement entity.

Methods, systems, apparatus and articles of manufacture to determine causal effects

A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values associated with the elements. The hash values specify bit positions within an array of bits. Hash values output from the hash logic conform to a geometric distribution such that bit positions of the array of bits corresponding to lower orders bits are more likely to be generated than bit positions corresponding to higher-order bits. Bits of the array of bits corresponding to the bit positions are set. The number of bits of the array of bits that are set is counted. Estimation logic estimates the number of unique elements of the collection of elements as a function of the number of bits of the array of bits that are set.

Method and system for estimating the cardinality of information

Example methods, apparatus, systems, and articles of manufacture are disclosed for network-based monitoring and serving of media to in-vehicle occupants. An example method includes linking panelist data corresponding to media exposure to first telemetry data collected by a vehicle to create linked panelist-telemetry data; and training a neural network to estimate vehicle occupant demographics based on second telemetry data using a first subgroup of the linked panelist-telemetry data.

Methods and apparatus for network-based monitoring and serving of media to in-vehicle occupants

Methods, apparatus, systems, and articles of manufacture are disclosed to estimate an audience population. An example apparatus includes processor circuitry; characteristic identifier instructions to be executed by the processor circuitry to determine whether respective ones of respondents are associated with a characteristic; recapture probability estimator instructions to be executed by the processor circuitry to select a recapture probability of the respective ones of respondents; and population estimator instructions to be executed by the processor circuitry to in response to the recapture probability satisfying a recapture threshold, determine a population estimate having the characteristics based on a first model; and in response to the recapture probability not satisfying the recapture threshold, determine the population estimate having the characteristics based on a second model, the second model different than the first model.

Methods, systems, articles of manufacture, and apparatus to estimate audience population

Methods, apparatus, systems, and articles of manufacture to identify inconsistencies in audience measurement data are disclosed. Example apparatus disclosed herein are to compare ones of a first set of cumulative audience metrics with one or more limits based on a second set of event-level audience metrics to detect an inconsistency in at least one of the first set of cumulative audience metrics or the second set of event-level audience metrics. Disclosed example apparatus are further to generate a report of the inconsistency in the at least one of the first set of event-level audience metrics or the second set of cumulative audience metrics.

Methods and apparatus to identify inconsistencies in audience measurement data

Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assign respondents to geographic locations for audience measurement are disclosed. Example apparatus disclosed herein are to determine a set of constraints based on aggregate values of demographic features associated with respective ones of the geographic locations. Disclosed example apparatus are also to construct a model to return probabilities that respective ones the respondents are associated with the respective ones of the geographic locations, the model to have a set of parameters, respective ones of the parameters to be associated with respective ones of the constraints. Disclosed example apparatus are further to evaluate the model based on values of the set of parameters and values of the demographic features for a first one of the respondents to determine a set of probabilities that the first respondent is to be assigned to respective ones of the geographic locations.

Assigning synthetic respondents to geographic locations for audience measurement

Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes memory and processor circuitry to determine a population reach estimate of a union of time intervals for which media ratings data is available, the population reach estimate based on a pseudo universe estimate of a population audience corresponding to the union of the time intervals; determine a pseudo universe estimate of a recorded audience corresponding to the union of the time intervals; determine the pseudo universe estimate of the population audience based on the pseudo universe estimate of the recorded audience; and in response to a decision to update the pseudo universe estimate of the population audience to reduce an error of the population reach estimate output the population reach estimate of the union when the error of the population reach estimate satisfies a threshold.

Methods and apparatus to estimate population reach from different marginal rating unions

A disclosed example includes: at least one memory; instructions; and processor circuitry to execute the instructions to at least: determine a first sum of estimated individual cardinalities of audience members of first and second media platforms; determine a second sum of estimated pairwise cardinalities of ones of the audience members belonging to both the first and second media platforms; and generate lower and upper bound estimates of a deduplicated audience size based on the first and second sums; and send the deduplicated audience size to a computing device via a network communication.

Methods and apparatus to estimate unique audience sizes across multiple intersecting platforms

A disclosed example includes determining a plurality of cross-demographic total census parameter values based on ratios of third-party impression counts and third-party audience sizes, selecting a first cross-demographic total census parameter value as an upper bound constraint from the plurality of cross-demographic total census parameter values based on comparisons between ones of the plurality of cross-demographic total census parameter values, selecting a second cross-demographic total census parameter value from the plurality of cross-demographic total census parameter values based on the second cross-demographic total census parameter value being less than the upper bound constraint, determining a first census-level audience size based on the second cross-demographic total census parameter value, and determining a first census-level impression count based on the second cross-demographic total census parameter value.

Methods and apparatus to estimate census level impressions and unique audience sizes across demographics

An example apparatus includes an audience size calculator circuitry to determine a first census-level audience size, and an impression count calculator circuitry to determine a first census-level impression count. The example apparatus includes a verification controller circuitry to determine whether the first one of the plurality of cross-demographic total census audience parameter values satisfies a first constraint; determine the first one of the plurality of cross-demographic total census impression parameter values satisfies a second constraint based on the first census-level impression count; and when the first constraint is not satisfied or the second constraint is not satisfied: (a) discard the first one of the cross-demographic total census audience parameter values and the first one of the cross-demographic total census impression parameter values, and (b) select a second one of the cross-demographic total census audience parameter values and a second one of the cross-demographic total census impression parameter values.

Methods and apparatus to estimate census level impression counts and unique audience sizes across demographics

Methods, apparatus, systems, and articles of manufacture are disclosed to determine unique audience size via clustered data. An example apparatus includes memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions. The example processor circuitry is to form a first matrix identifying matching and non-matching instances of first values of respective demographics of an audience of media and second values of the respective demographics. Also, the processor circuitry is to normalize the first matrix to generate an account sharing adjustment matrix. Additionally, the processor circuitry is to apply the account sharing adjustment matrix to a vector of one or more counts of impressions of the media to correct for one or more members of the audience that share a user account registered with a database proprietor, the one or more counts of the impressions corresponding to the respective demographics.

Methods, apparatus, and articles of manufacture to determine unique audience size via clustered data

A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.

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North Stonington, CT, United States of America

Edward Murphy