Abstract: Methods, apparatus, systems to determine a conditional probability based on audience member probability distributions for media audience measurement are disclosed. Disclosed example methods for media audience measurement include determining a first audience probability distribution for a first member of a household and determining a second audience probability distribution for a second member of the household. Disclosed example methods also include calculating probabilities for audience combinations of the first member and the second member of the household based on the first audience probability distribution and the second audience probability distribution. Disclosed example methods further include determining a household audience characteristic probability based on the calculated probabilities of the audience combinations of the household. The household audience characteristic indicates likelihoods of different possible audience compositions of the household for a media event.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand and dynamically inserted advertisement viewing probability.

Abstract: Methods and apparatus to determine ratings data from population sample data having unreliable demographic classifications are disclosed. An example method includes receiving, at an audience measurement entity (AME), a first request sent from a first type of device via a communications network; sending a request for demographic information corresponding to requests received at the AME from the first type of device, the requests including the first request; obtaining a misattribution matrix; generating a multinomial distribution from the misattribution matrix; generating samples of the multinomial distribution; converting the samples to misattribution matrices; and applying a vector to the plurality of misattribution matrices to estimate a first number of audience members who are attributable to the second demographic group, the vector representing a second number of audience members who are associated with the first demographic group based on the demographic information.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed. An example method of reducing memory usage of a computing device disclosed herein comprises storing a constraint matrix and a population matrix into a memory, the population matrix representing a population related to data of the constraint matrix, determining, via a processor, a linear system based on a set of constraints including the constraint matrix and the population matrix, determining, via a processor, an inverse of a matrix of the linear system, the determination of the inverse including breaking down the matrix into blocks, the dimensions of the blocks being no larger than dimensions of the constraint matrix, and outputting a set of weights based on the inverse of the linear system, the set of weights satisfying the set of constraints.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand and dynamically inserted advertisement viewing probability.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve reach calculation efficiency. An example method includes estimating, with a processor, a sample distribution of marketing data to generate a maximum entropy distribution, generating, with the processor, a geometric distribution based on estimating a minimum cross entropy of (a) the maximum entropy distribution and (b) the sample distribution of marketing data, and improving calculation efficiency of the public reach of the sample distribution of marketing data by generating, with the processor, conserved quantity expressions of the geometric distribution.

Abstract: Methods and apparatus to estimate demography based on aerial images are disclosed. An example method includes analyzing a first aerial image of a first geographic area to detect a first plurality of objects, analyzing a second aerial image of a second geographic area to detect a second plurality of objects, associating first demographic information to the second plurality of objects, the first demographic information obtained by a sampling of the second geographic area, and comparing the second plurality of objects to the first plurality of objects to estimate a demographic characteristic of the first geographic area based on the comparison.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand viewing probability.

Abstract: Examples to determine media impressions are disclosed. An example method includes determining an exposure of first media, wherein the exposure occurs after a cookie identifier is received at a computing device, wherein the cookie identifier is received from a database proprietor, determining a first panelist identifier associated with the exposure based on the cookie identifier, determining a second panelist identifier associated with the exposure based on a determination of a user identity by a panelist meter associated with the computing device, determining an adjustment factor by comparing the first panelist identifier and the second panelist identifier, determining a number of impressions of second media from data logged by the database proprietor, the data logged in response to requests transmitted to the database proprietor in response to clients accessing the second media, and applying the adjustment factor to the number of impressions to determine an adjusted number of impressions.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand viewing probability.

Abstract: Methods and apparatus to estimate commercial characteristics based on aerial images are disclosed. An example method includes identifying, using a computer vision technique, a feature in a first aerial image of a geographic location of interest, identifying a reference aerial image that includes the feature from a set of reference aerial images, the reference aerial image being associated with commercial characteristics, and associating a first one of the commercial characteristics with the location of interest.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand viewing probability.

Abstract: Methods and apparatus to estimate demography based on aerial images are disclosed. An example method includes analyzing a first aerial image of a first geographic area to detect a first plurality of objects, analyzing a second aerial image of a second geographic area to detect a second plurality of objects, associating first demographic information to the second plurality of objects, the first demographic information obtained by a sampling of the second geographic area, and comparing the second plurality of objects to the first plurality of objects to estimate a demographic characteristic of the first geographic area based on the comparison.

Abstract: Examples to determine media impressions are disclosed. An example method includes detecting a cookie identifier established by a database proprietor at a computing device, determining an impression of media, wherein the impression occurs after the cookie identifier is established, determining a first panelist identifier associated with the impression based on the cookie identifier, determining a second panelist identifier associated with the impression based on determination of a user identity by a panelist meter associated with the computing device, and storing an adjustment factor determined by comparing the first panelist identifier and the second panelist identifier.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to calculate video-on-demand viewing probability.

Abstract: Methods and apparatus to estimate demography based on aerial images are disclosed. An example method includes analyzing a first aerial image of a first geographic area to detect a first plurality of objects, and estimating a demographic characteristic of the first geographic area based on the first plurality of objects.

Abstract: Methods and apparatus to count audience members are disclosed. An example method includes determining a first viewing count of a number of times that a first person was historically logged in to a measurement apparatus during a day part; determining a second viewing count of a number of times that a second person was historically logged in to the measurement apparatus during the day part; determining, using a processor, a first probability that the first person is in a current audience based on the first viewing count and the second viewing count; and when the first probability satisfies a probability threshold, prompting the audience to enter user identification.

Abstract: Examples to determine media impressions are disclosed. An example method includes detecting a cookie identifier established by a database proprietor at a computing device, determining an impression of media, wherein the impression occurs after the cookie identifier is established, determining a first panelist identifier associated with the impression based on the cookie identifier, determining a second panelist identifier associated with the impression based on determination of a user identity by a panelist meter associated with the computing device, and storing an adjustment factor determined by comparing the first panelist identifier and the second panelist identifier.

Abstract: A disclosed example method to determine audience duplication in cross-media campaigns involves determining a first duplicated audience reach for a demographic group between a total television audience and an internet publisher audience. The total television audience is representative of audience members across a plurality of television networks. The internet publisher audience is representative of audience members of one of a plurality of internet publishers. The example method involves determining a second duplicated audience reach between the total television audience and the internet publisher audience for a media campaign based on the first duplicated audience reach. The example method involves determining a third duplicated audience reach between a television network audience and the internet publisher audience for the media campaign based on the second duplicated audience reach.

Abstract: A disclosed example method to determine audience duplication in cross-media campaigns involves determining a first duplicated audience reach between a total television audience and an internet publisher audience for a demographic group. The total television audience is representative of audience members across a plurality of television networks, and the internet publisher audience is representative of audience members across one of a plurality of internet publishers. The example method involves determining a second duplicated audience reach between the total television audience and the internet publisher audience for a media campaign based on the first duplicated audience reach. The example method involves determining a third duplicated audience reach between a television network audience and the internet publisher audience for the media campaign based on the second duplicated audience reach.