Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An example apparatus includes memory, programmable circuitry, and instructions in the memory, the instructions to cause the programmable circuitry to at least access impression data associated with a user account registered with a database proprietor, the user account associated with first demographics at a database of the database proprietor. The example programmable circuitry is also to determine a primary user of the user account based on the impression data and based on second demographics of multiple users of the user account, the multiple users including the primary user. Additionally, the example programmable circuitry is to modify the first demographics associated with the user account based on at least some of the second demographics, the at least some of the second demographics corresponding to the primary user.

Abstract: An example apparatus disclosed herein includes a data input interface to access different sets of initial adjustment factors, the initial adjustment factors generated to correct at least one of misattribution or non-coverage of media impressions logged by a database proprietor, a grouping controller to identify a first set of the initial adjustment factors as a set of donor adjustment factors based on (a) first audience members associated with the set of donor adjustment factors satisfying a first threshold and (b) first impressions associated with the first audience members satisfying a second threshold, and identify a second set of the initial adjustment factors as a set of recipient adjustment factors, and an imputation factor generator to generate imputation factors to correct ones of the recipient adjustment factors based on ones of the donor adjustment factors.

Abstract: Disclosed examples access media impression data via one or more wireless communications, the media impression data including panel data obtained from a meter and impression information obtained after an access of media at a computing device; determine an audience deduplication based on the panel data; determine odds ratios for platform combinations based on the audience deduplication; determine posterior distributions for the media based on the odds ratios; perform a sequential odds ratio insertion technique based on the posterior distributions to determine unique audience sizes; align the unique audience sizes based on a constraint; and generate a report including the aligned unique audience sizes.

Abstract: Methods, apparatus, and systems are disclosed for audience-based deduplication using vector-of-counts (VOC) central moments. An example system to determine an audience size for media based on vector of counts sketch data, the system including memory, programmable circuitry, and instructions to cause the programmable circuitry to apply a hash function to first vector of counts sketch data, second vector of counts sketch data, and third vector of counts sketch data to remove personally identifiable information, determine a first covariance matrix associated with intersection cardinalities of at least two of the first, second, or third vector of counts, determine a second covariance matrix associated with disjoint cardinalities of the at least two of the first, second, or third vector of counts, and determine the audience size based on the first covariance matrix or the second covariance matrix.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. An example apparatus includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to generate a first demographic correction model based on a first matrix, the first matrix including first data indicative of user accesses to media, the first matrix associated with a first demographic, generate a second demographic correction model based on a second matrix, the second matrix including second data indicative of user accesses to the media, the second matrix associated with a second demographic, and generate predicted demographics of a user associated with the user accesses based on the first demographic correction model and the second demographic correction model, the predicted demographics including the first demographic and the second demographic.

Abstract: Methods and apparatus for multi-account adjustment in third-party privacy-protected cloud environments are disclosed herein. A disclosed example apparatus includes memory and processor circuitry to execute computer readable instructions to select a type of client device, determine a number of panelists associated with a demographic characteristic and the type of client device, the demographic characteristic defining a segment of the panelists, determine a number of user accounts associated with the number of panelists, determine a multi-account adjustment factor for the demographic characteristic and the client device based on a ratio of the number of the panelists to the number of user accounts, and adjust an initial estimate of a unique audience size based on the multi-account adjustment factor.

Abstract: An example system disclosed herein includes programmable circuitry to identify donor adjustment factors and recipient adjustment factors used for correction of media impressions logged by a database proprietor, the donor adjustment factors including first donor adjustment factors associated with a first geographic region and second donor adjustment factors associated with a second geographic region, determine a first reduced donor factor set corresponding to ones of the first donor adjustment factors that satisfy a threshold, determine a second reduced donor factor set corresponding to ones of the second donor adjustment factors that satisfy the threshold, and generate imputation factors based on an aggregation of retained ones of the donor adjustment factors, the retained ones of the donor adjustment factors selected based on the first reduced donor factor set and the second reduced donor factor set, the imputation factors to reduce error in the correction.

Abstract: An example system disclosed herein includes programmable circuitry to identify audience measurement panelists associated with database proprietor accounts, when a sign- out percentage of the audience measurement panelists is zero, determine a first probability that a second server of a database proprietor associated a first demographic with a logged impression when the logged impression corresponds to a second demographic, when the sign-out percentage of the audience measurement panelists is one hundred, determine a second probability that the second server of the database proprietor associated the first demographic with the logged impression when the logged impression corresponds to the second demographic, determine an adjustment factor based on a weighted combination of the first and second probabilities, and apply the adjustment factor to database proprietor impressions data to reduce a computer-generated error.

Abstract: A disclosed example includes aggregating first performance results of computer-generated machine learning models to generate aggregated performance results, the first performance results based on a comparison of audience member demographic data to training results, the training results generated by the computer-generated machine learning models based on at least one of: (a) a composition of a household, (b) a type of first media, (c) a daypart during which the first media was accessed, or (d) a time at which the first media was accessed; selecting at least one of the computer-generated machine learning models based on a comparison of ones of the first performance results to the aggregated performance results; and applying the at least one of the computer-generated machine learning models to correct a computer-generated error in computer-collected audience measurement data, the computer-collected audience measurement data corresponding to accesses to second media.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. In some examples, an apparatus comprising processor circuitry to execute the instructions to at least generate an individualization model based on truth data indicating first true users exposed to media via first panelist client devices, produce user probabilities for second panelist client devices based on the individualization model, the user probabilities indicating likelihoods of second true users being exposed to media via the second panelist client devices, select a user probability from the user probabilities based on an impression, and assign the impression to the set of second true users.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An example apparatus includes memory, programmable circuitry, and instructions in the memory, the instructions to cause the programmable circuitry to at least access impression data associated with a user account registered with a database proprietor, the user account associated with first demographics at a database of the database proprietor. The example programmable circuitry is also to determine a primary user of the user account based on the impression data and based on second demographics of multiple users of the user account, the multiple users including the primary user. Additionally, the example programmable circuitry is to modify the first demographics associated with the user account based on at least some of the second demographics, the at least some of the second demographics corresponding to the primary user.

Abstract: Disclosed examples to estimate audience sizes of media include a coefficient generator to determine coefficient values for a polynomial based on normalized weighted sums of variances, a normalized weighted sum of covariances, and cardinalities corresponding to a first plurality of vectors of counts from a first database proprietor and a second plurality of vectors of counts from a second database proprietor, a real roots solver to determine a real root value of the polynomial, the real root value indicative of a number of audience members represented in the first plurality of vectors of counts that are also represented in the second plurality of vectors of counts, and an audience size generator to determine the audience size based on the real root value and the cardinalities of the first plurality of vectors of counts and the second plurality of vectors of counts.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. An example apparatus includes a data modifier to obtain a first matrix, the first matrix including first data indicative of entities and embeddings, the entities representative of at least one of search result clicks or videos watched, the embeddings representative of at least one of first classifications of the search result clicks or second classifications of the videos watched, generate a second matrix by reducing the first data in the first matrix to second data that satisfies a size corresponding to an input feature, and store the second matrix in first memory as the input feature, and a model generator to generate a demographic correction model based on the second matrix as the input feature, the demographic correction model to correct demographics corresponding to impressions logged in second memory.

Abstract: Methods and apparatus for multi-account adjustment in third-party privacy-protected cloud environments are disclosed herein. A disclosed example apparatus includes memory and processor circuitry to execute computer readable instructions to select a demographic characteristic, the demographic characteristic defining a segment of panelists, select a type of client device, determine a number of the panelists associated with the demographic characteristic and the client device, and define a multi-account adjustment factor for the demographic characteristic and the client device, the factor based on a ratio of a number of panelists to a number of user accounts, the user accounts associated with the determined number of panelists.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An apparatus comprising: memory; and processor circuitry to execute instructions that causes the processor circuitry to at least: determine a first total score for a first panelist associated with a panelist user account based on at least one of a first impression score, a first age score, or a first gender score; determine a second total score for a second panelist associated with the panelist user account based on at least one of a second impression score, a second age score, or a second gender score; and in response to determining that the first total score satisfies a threshold, store demographics of the first panelist for the panelist user account.

Abstract: An example apparatus disclosed herein includes a panelist detector to identify audience measurement panelists associated with database proprietor accounts, a sign-in rate calculator to determine an actual sign-in rate of the audience measurement panelists based on first impressions represented in database proprietor impressions data and second impressions represented in panel data, an adjustment factor generator to determine a first audience adjustment factor corresponding to a first sign-in rate and a second audience adjustment factor corresponding to a second sign-in rate, and a weighting controller to generate a first weighted audience adjustment factor and a second weighted audience adjustment factor by weighting the first and second audience adjustment factors by the actual sign-in rate, the adjustment factor generator to determine a signed-out adjustment factor based on the first and second weighted audience adjustment factors.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to generate computer-trained machine learning models to correct computer-generated errors in audience data. An example apparatus includes a query selector to select a plurality of features and a range of hyperparameters; a query generator to generate a plurality of machine learning models based on the plurality of features and the range of hyperparameters, and initiate training of the plurality of machine learning models based on demographic data in a privacy-protected cloud environment, the demographic data obtained from database proprietor user accounts corresponding to audience measurement panelists; and a model selector to select a first machine learning model from the plurality of machine learning models.

Abstract: An example apparatus disclosed herein includes a data input interface to access different sets of initial adjustment factors, the initial adjustment factors generated to correct at least one of misattribution or non-coverage of media impressions logged by a database proprietor, a grouping controller to identify a first set of the initial adjustment factors as a set of donor adjustment factors based on (a) first audience members associated with the set of donor adjustment factors satisfying a first threshold and (b) first impressions associated with the first audience members satisfying a second threshold, and identify a second set of the initial adjustment factors as a set of recipient adjustment factors, and an imputation factor generator to generate imputation factors to correct ones of the recipient adjustment factors based on ones of the donor adjustment factors.