Abstract: Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. Example instructions cause a machine to at least, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; obtain a count of demographic impressions logged by a database proprietor; obtain a count of registered users of the database proprietor exposed to the media; and execute a process to determine a unique audience size by multiplying a count of the plurality of impressions by a square of the count of the registered users to generate a product; dividing the product by the count of the demographic impressions to generate a quotient; and determining the unique audience size based on a square root of the quotient.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to correct segmentation errors. An example disclosed method includes identifying, with a processor, a segment group comprising observation data associated with two or more segments, respective ones of the two or more segments having a similar first characteristic and a dissimilar second characteristic, identifying first portions of the observation data having errors, generating a first matrix of binary indicators associated with the observation data, the binary indicators associating the first portions of the observation data with a first correction factor, and generating a value for the first correction factor by minimizing a residual sum of squares of the segment group observation data associated with the first matrix of binary indicators.

Abstract: Methods and apparatus to calculate granular data of a region based on another region for media audience measurement are disclosed. An example method for calculating, via a processor, granular data of a region includes determining aggregate behavioral data associated with a media audience measurement of a target region. The example method includes determining, via the processor, aggregate demographics data of the target region. The example method includes determining, via the processor, granular data of a source region. The example method includes calculating, via the processor, granular data of the target region to measure a media audience of the target region by apportioning the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to determine a duration of media presentation based on tuning session duration. Example apparatus include a tuning session determiner to determine a first tuning session based on a period of time between channel changes of a first media presentation device; a presentation session determiner to determine first presentation session data within the determined first tuning session; a modeler to determine a model by relating the first tuning session with the first presentation session data; a receiver to determine a second tuning session for tuning data from a second media presentation device; and a presentation session estimator to: select the model for the second tuning session, based on a match of a first duration of the second tuning session and a second duration associated with the model, and estimate second presentation session data for the second tuning session based on the model.

Abstract: Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. Example instructions cause a machine to at least, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; obtain a count of demographic impressions logged by a database proprietor; obtain a count of registered users of the database proprietor exposed to the media; and execute a process to determine a unique audience size by multiplying a count of the plurality of impressions by a square of the count of the registered users to generate a product; dividing the product by the count of the demographic impressions to generate a quotient; and determining the unique audience size based on a square root of the quotient.

Abstract: Methods and apparatus to calculate granular data of a region based on another region for media audience measurement are disclosed. An example method for calculating, via a processor, granular data of a region includes determining aggregate behavioral data associated with a media audience measurement of a target region. The example method includes determining, via the processor, aggregate demographics data of the target region. The example method includes determining, via the processor, granular data of a source region. The example method includes calculating, via the processor, granular data of the target region to measure a media audience of the target region by apportioning the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve decision tree execution. An example method includes retrieving, with a processor, a decision tree logic expression in a sum-of-products (SOP) form, the decision tree logic expression consuming a first duration to evaluate a dataset, eliminating, with the processor, redundant variables of the decision tree logic expression by transforming the decision tree logic expression into a product-of-sums (POS) form, and evaluating, with the processor, the data set with the decision tree logic expression in the POS form, the decision tree logic expression in the POS form consuming a second duration to evaluate the data set that is less than the first duration.

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 demographics of a household are disclosed. An example method to determine demographics for non-panelist households includes calculating a first demographic constraint average and a second demographic constraint average based on a first demographic distribution of a first tuning event of a household and a second demographic distribution of a second tuning event of the household. The household is a non-panelist household. The example method also includes, based on the first demographic constraint average, determining a first likelihood of the household being associated with a first demographic constraint. The example method also includes, based on the second demographic constraint average, determining a second likelihood of the household being associated with a second demographic constraint. The example method also includes estimating a household characteristic of the household based on the first likelihood and the second likelihood.

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.

Abstract: Methods and apparatus to utilize a minimum cross entropy to calculate granular data of a region based on another region for media audience measurement. An example method for calculating granular data of a region for media audience measurement includes determining, by executing first instructions via a processor, aggregate behavioral data associated with a measurement of a media audience of a target region; determining, by executing second instructions via the processor, aggregate demographics data of the target region; and determining, by executing third instructions via the processor, granular data of a source region. The example method includes calculating, by executing fourth instructions via the processor, granular data of the media audience of the target region by utilizing minimum cross entropy to apportion the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region to determine.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve decision tree execution. An example method includes retrieving, with a processor, a decision tree logic expression in a sum-of-products (SOP) form, the decision tree logic expression consuming a first duration to evaluate a dataset, eliminating, with the processor, redundant variables of the decision tree logic expression by transforming the decision tree logic expression into a product-of-sums (POS) form, and evaluating, with the processor, the data set with the decision tree logic expression in the POS form, the decision tree logic expression in the POS form consuming a second duration to evaluate the data set that is less than the first duration.

Abstract: Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. Example instructions cause a machine to at least, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; obtain a count of demographic impressions logged by a database proprietor; obtain a count of registered users of the database proprietor exposed to the media; and execute a process to determine a unique audience size by multiplying a count of the plurality of impressions by a square of the count of the registered users to generate a product; dividing the product by the count of the demographic impressions to generate a quotient; and determining the unique audience size based on a square root of the quotient.

Abstract: Methods and apparatus to calculate granular data of a region based on another region for media audience measurement are disclosed. An example method for calculating, via a processor, granular data of a region includes determining aggregate behavioral data associated with a media audience measurement of a target region. The example method includes determining, via the processor, aggregate demographics data of the target region. The example method includes determining, via the processor, granular data of a source region. The example method includes calculating, via the processor, granular data of the target region to measure a media audience of the target region by apportioning the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region.

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 and apparatus to estimate demographics of a household are disclosed. An example method to determine demographics for non-panelist households includes calculating a first demographic constraint average and a second demographic constraint average based on a first demographic distribution of a first tuning event of a household and a second demographic distribution of a second tuning event of the household. The household is a non-panelist household. The example method also includes, based on the first demographic constraint average, determining a first likelihood of the household being associated with a first demographic constraint. The example method also includes, based on the second demographic constraint average, determining a second likelihood of the household being associated with a second demographic constraint. The example method also includes estimating a household characteristic of the household based on the first likelihood and the second likelihood.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify co-relationships between media using social media. An example apparatus includes an audience estimator to: estimate a first audience of first media based on a first set of media-exposure social media messages corresponding to client devices referencing the first media, and estimate a second audience of second media based on a second set of media-exposure social media messages corresponding to the client devices referencing the second media.

Abstract: Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. An example method includes receiving impression requests at a server from a plurality of client devices via a network; based on the impression requests, logging, with the server, a plurality of impressions corresponding to the media accessed at the client devices; obtaining a number of demographic impressions logged by a database proprietor; obtaining a number of registered users of the database proprietor exposed to the media; multiplying, by executing an instruction with a processor, a number of the plurality of impressions by a square of the number of the registered users to generate a product; dividing, by executing an instruction with the processor, the product by a number of the demographic impressions to generate a quotient; and determining, by executing an instruction with the processor, the unique audience based on a square root of the quotient.

Abstract: Methods and apparatus to utilize a minimum cross entropy to calculate granular data of a region based on another region for media audience measurement. An example method for calculating granular data of a region for media audience measurement includes determining, by executing first instructions via a processor, aggregate behavioral data associated with a measurement of a media audience of a target region; determining, by executing second instructions via the processor, aggregate demographics data of the target region; and determining, by executing third instructions via the processor, granular data of a source region. The example method includes calculating, by executing fourth instructions via the processor, granular data of the media audience of the target region by utilizing minimum cross entropy to apportion the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region to determine.

Abstract: Methods and apparatus to apply household-level weights to audience measurement data at a household-member level are disclosed. An example method to determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population. First demographics of a first member of the first household are different than second demographics of a second member of the first household. The example method includes calculating a first household-level weight for the first household based on a demographics distribution of the sub-population and aggregate demographics of a population.