The Nielsen Comapny (us), LLC

Jake Ryan Dailey

Diane Morovati Lopez

Michael R Sheppard

Jonathan Lee Sullivan

Molly Poppie

Christie Nicole Summers

Damien Forthomme

Dongbo Cui

Jessica D Brinson

Chris Nicotra

Christine Pierce

Jose Mortensen

Furqan Hanif

Matthew Vanlandeghem

Edward Murphy

DongBo Cui

Ludo Daemen

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.

Methods and apparatus to estimate audience sizes of media using deduplication based on multiple vectors of counts

Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate de-duplicated unknown total audience sizes based on partial information of known audiences. An example apparatus includes an association controller to generate a tree structure association corresponding to a union of first and second margins of time; and one or more commercial solvers to: perform parallel computations on a processor to determine multipliers by solving equations corresponding to the tree structure association, the multipliers corresponding to the first total audience size for the union, the second total audience size for the first margin, and the third total audience size for the second margin; and determine an estimate for the third total audience size for the second margin of time based on the multipliers.

Methods and apparatus to estimate de-duplicated unknown total audience sizes based on partial information of known audiences

Methods, apparatus, systems, and articles of manufacture to estimate cardinality of users represented in arbitrarily distributed bloom filter arrays are disclosed. A system includes a communication interface to: access a first Bloom filter array representative of first entries in a first database, the first entries allocated to ones of first elements in the first Bloom filter array based on a non-uniform distribution of outputs of a hash function applied to the first entries, and access a second Bloom filter array representative of second entries in a second database. The system also includes machine readable instructions to cause one or more processors to estimate a cardinality of a union of the first and second entries based on the non-uniform distribution of the outputs of the hash function.

Methods and apparatus to estimate cardinality of users represented in arbitrarily distributed bloom filters

Methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach from marginals. An example apparatus includes memory including computer readable instructions; and a processor to execute the instructions to: iteratively converge on an output estimate of a pseudo universe estimate of a recorded audience of first media based on (A) a recorded reach for the recorded audience of the first media and (B) first marginal ratings for the recorded audience of the first media; determine a panel representation value based on the pseudo universe estimate of the recorded audience of the first media; and iteratively converge on an output estimate of a final reach of second media for a population audience based on the panel representation value and second marginal ratings for the population audience of the second media.

Methods and apparatus to estimate population reach from marginals

Methods and apparatus to estimate audience sizes using deduplication based on binomial sketch data are disclosed. An apparatus includes processor circuitry to instantiate coefficient analyzer circuitry to determine coefficient values of a polynomial based on (i) variances in values in the first sketch data and second sketch data, (ii) a first cardinality of the first sketch data, and (iii) a second cardinality of the second sketch data. The processor circuitry to instantiate overlap analyzer circuitry to determine a real root of the polynomial, the real root corresponding to the quantity of the second subscribers that are duplicates of the first subscribers. The processor circuitry to instantiate report generator circuitry to estimate a deduplicated audience size based on the estimate of the quantity of the second subscribers that are duplicates of the first subscribers and the first and second cardinalities.

Methods and apparatus to estimate audience sizes of media using deduplication based on binomial sketch data

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 and apparatus to estimate audience sizes and durations for media accesses are disclosed. An example apparatus at least one memory, instructions, and processor circuitry to execute the instructions to select constraint equations corresponding to one or more events, the one or more events corresponding to a first audience and a second audience, the first audience to include the second audience, and determine, based on the constraint equations and an auxiliary equation, event audience sizes corresponding to the first audience and to the one or more events.

Methods and apparatus to estimate audience sizes and durations of media accesses

Methods and apparatus to estimate audience sizes using deduplication based on vector of counts sketch data are disclosed. A system includes hardware circuitry to instantiate: coefficient analyzer circuitry to determine coefficient values of a polynomial based on (i) variances in values in a first vector of counts and a second vector of counts, (ii) a first cardinality of the first vector of counts, and (iii) a second cardinality of the second vector of counts; and overlap analyzer circuitry to: determine a real root of the polynomial; and report generator circuitry to estimate a deduplicated audience size based on (i) the estimate of the quantity of the second subscribers that are duplicates of the first subscribers and (ii) the first and second cardinalities. The system includes communication circuitry to transmit a network communication to a third party entity, the second network communication including a report based on the deduplicated audience size.

Methods and apparatus to estimate audience sizes of media using deduplication based on vector of counts sketch data

An example apparatus disclosed herein includes at least one memory, instructions, and at least one processor to execute the instructions to: receive first HyperLogLog (HLL) data from a first server of a first database proprietor and second HyperLogLog (HLL) data from a second server of a second database proprietor, the first HLL data including obfuscated first user impression data and the second HLL data including obfuscated second user impression data; generate union HLL data based on the first HLL data from the first database proprietor and the second HLL data from the second database proprietor by performing a union of data sets of the obfuscated first user impression data represented in the first HLL data and the obfuscated second user impression data represented in the second HLL data; and determine a total number of deduplicated unique audience members based on the union HLL data generated by the vector analyzer.

Methods and apparatus to determine a unique audience for internet-based media

Example technical solutions to determine census-level audience metrics across demographics are disclosed. Disclosed example apparatus include a distribution parameter solver to initialize distribution parameter values for a probability of an individual within a demographic being (i) included in a subscriber audience for the demographic and (ii) having a first impression duration, the subscriber audience having a first subscriber audience size. Disclosed example apparatus also include a divergence parameter solver to determine divergence parameter values between (i) the first subscriber audience size and the first impression duration and (ii) a census-level audience size and a second impression duration based on the initialized distribution parameter values. Disclosed example apparatus further include a search space identifier to identify a search space within bounds based on a census-level total impression count and a census-level total impression duration, the search space to define a range based on census-level duration equality and census-level audience equality constraints.

Methods, systems and apparatus to estimate census-level total impression durations and audience size across demographics

Methods and apparatus to estimate cardinality of users represented across multiple bloom filter arrays are disclosed. Examples includes processor circuitry to execute and/or instantiate instructions to generate a first composite Bloom filter array based on first and second Bloom filter arrays. The processor circuitry is to generate a final composite Bloom filter array based on the first composite Bloom filter array and a third Bloom filter array. Different ones of the first, second, and third Bloom filter arrays representative of different sets of users who accessed media. The first, second, and third Bloom filter arrays including differential privacy noise. The processor circuitry to estimate a cardinality of a union of the first, second, and third Bloom filter arrays based on the final composite Bloom filter array.

Methods and apparatus to estimate cardinality of users represented across multiple bloom filter arrays

Methods and apparatus to estimate cardinality across multiple datasets represented using Bloom filter arrays are disclosed. Disclosed examples include processor circuitry to execute and/or instantiate instructions to determine an inclusion-exclusion expression that defines an audience size for a user group of interest. Terms in the inclusion-exclusion expression corresponding to either a first cardinality of a first one of at least three Bloom filter arrays or a second cardinality of a union of two or more of the Bloom filter arrays. Different ones of the Bloom filter arrays representative of different sets of users who accessed media. The at least one processor further to estimate, based on the inclusion-exclusion expression, the audience size of the user group of interest.

Methods and apparatus to estimate cardinality across multiple datasets represented using bloom filter arrays

Methods, apparatus, systems, and articles of manufacture to estimate audience measurement metrics based on users represented in Bloom filter arrays are disclosed. An apparatus includes a communications interface to receive a first Bloom filter array from a first computer of a first database proprietor. The first Bloom filter array is representative of first users who accessed media. The first users are registered with the first database proprietor. The first Bloom filter array includes a first array of first elements. Values of respective ones of the first elements are either a 0 or a 1 based on whether quantities of the first users allocated to the respective ones of the first elements are even or odd. The apparatus further includes a Bloom filter array analyzer to estimate a first cardinality for the first Bloom filter array. The first cardinality is indicative of a total number of the first users who accessed the media.

Growing community of inventors

San Francisco, CA, United States of America

Jake Ryan Dailey