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, 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.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to generate measures of unique audiences for Internet-based media.

Abstract: Methods, apparatus, and articles of manufacture to correct misattributions of media impressions are disclosed. An example method includes obtaining first demographic-based impressions via a beacon transmitted in response to access to content by a first set of panelists, obtaining, from a database proprietor, second demographic-based impressions of the content on a second set of persons, forming a pseudo-inverse matrix determined based in part on the first impressions, and having a truncated value and a damped value to form third demographic-based impressions of the content on the second set of persons based on the second impressions, and computing at least partially corrected demographic-based impressions values by multiplying a vector of database proprietor impression data by the pseudo-inverse matrix.

Abstract: Methods, apparatus, and articles of manufacture to correct misattributions of media impressions are disclosed. An example method includes obtaining first demographic-based impressions via a beacon transmitted in response to access to content by a first set of panelists, obtaining, from a database proprietor, second demographic-based impressions of the content on a second set of persons, forming a pseudo-inverse matrix determined based in part on the first impressions, and having a truncated value and a damped value to form third demographic-based impressions of the content on the second set of persons based on the second impressions, and computing at least partially corrected demographic-based impressions values by multiplying a vector of database proprietor impression data by the pseudo-inverse matrix.

Abstract: Methods, apparatus, and articles of manufacture to correct misattributions of media impressions are disclosed. An example method includes obtaining first demographic-based impressions via a beacon transmitted in response to access to content by a first set of panelists, obtaining, from a database proprietor, second demographic-based impressions of the content on a second set of persons, forming a pseudo-inverse matrix determined based in part on the first impressions, and having a truncated value and a damped value to form third demographic-based impressions of the content on the second set of persons based on the second impressions, and computing at least partially corrected demographic-based impressions values by multiplying a vector of database proprietor impression data by the pseudo-inverse matrix.

Abstract: Methods, apparatus, and articles of manufacture to correct misattributions of media impressions are disclosed. An example method includes obtaining first demographic-based impressions via a beacon transmitted in response to access to content by a first set of panelists, obtaining, from a database proprietor, second demographic-based impressions of the content on a second set of persons, forming a pseudo-inverse matrix determined based in part on the first impressions, and having a truncated value and a damped value to form third demographic-based impressions of the content on the second set of persons based on the second impressions, and computing at least partially corrected demographic-based impressions values by multiplying a vector of database proprietor impression data by the pseudo-inverse matrix.

Abstract: Methods, apparatus, and articles of manufacture are disclosed. An example apparatus includes a co-viewing calculator to calculate a co-viewing factor corresponding to a demographic of panelists based on exposure information, an exposure time calculator to calculate a number of census co-viewer exposure minutes based on the co-viewing factor, a data aggregator to determine an aggregate exposure time total based on census exposure information and the number of census co-viewer exposure minutes, and a report generator to generate a report including the aggregate exposure time total.