Methods and apparatus to estimate an unknown audience size from recorded demographic impressions

Patent metadata

Field	Value
Publication number	US-2016379246-A1
Application number	US-201514752441-A
Country	US
Kind code	A1
Filing date	Jun 26, 2015
Priority date	Jun 26, 2015
Publication date	Dec 29, 2016
Grant date	—

Abstract

Methods, apparatus, systems and articles of manufacture are disclosed to estimate an unknown audience size from recorded impressions for an online media. The estimate of the unknown audience size for the online media is based on a total number of initial impressions and a frequency distribution of recorded demographic impressions across a partial audience size for the online media. The estimate of the unknown audience size is determined by modeling the probability of obtaining the frequency distribution of the recorded demographic impressions across the partial audience for different possible unknown audience sizes in a range of unknown audience sizes and determining an estimate for the unknown audience size by evaluating the models for the different possible unknown audience sizes.

First claim

1 . A method of estimating an unknown audience size from recorded demographic impressions for an online media, the method comprising:
accessing, for the online media, a total number of initial impressions and a frequency distribution of the recorded demographic impressions across a partial audience size; determining, with a processor and based on the total number of initial impressions and the frequency distribution of the recorded demographic impressions across the partial audience, models modeling a probability of obtaining the frequency distribution of the recorded demographic impressions across the partial audience for different possible unknown audience sizes in a range of unknown audience sizes; determining, with the processor, an estimate for the unknown audience size by evaluating the models for the different possible unknown audience sizes.

2 . The method of claim 1 , further including:
assigning the estimate as an actual audience size for the online media.

3 . The method of claim 1 , wherein the frequency distribution of the recorded demographic impressions across the partial audience is received from a database proprietor.

4 . The method of claim 3 , wherein the database proprietor includes at least one of a social network service provider, a multi-service service provider, a streaming media service provider, an online shopping service provider, or a credit reporting service provider.

5 . The method of claim 3 , wherein the frequency distribution of the recorded demographic impressions across the partial audience is received from the database proprietor in response to sending a list of the total number of initial impressions for the online media to the database proprietor.

6 . The method of claim 1 , wherein the models are based on Beta-Binomial Distributions.

7 . The method of claim 1 , wherein the total number of initial impressions are modeled as being distributed across a first possible unknown audience having a first possible unknown audience size via a Dirichlet-Multinomial Distribution.

8 . The method of claim 7 , wherein the Dirichlet-Multinomial Distribution is symmetric.

9 . The method of claim 8 , wherein the model of the Dirichlet-Multinomial Distribution is modified by adding one initial impression to each person in the unknown audience such that the number of initial impressions for each person follows a shifted Beta Binomial distribution.

10 . The method of claim 1 , wherein a probability of a demographic impression being recorded for an individual is modeled as a Beta Binomial Distribution.

11 . The method of claim 1 , wherein the determining of the estimate for the unknown audience size includes evaluating log-likelihood metrics for respective ones of the models using the frequency distribution of recorded demographic impressions across the partial audience, selecting one of the models based on the log-likelihood, and selecting a respective one of the possible unknown audience sizes corresponding to the selected model to be the estimate for the unknown audience size.

12 . The method of claim 1 , wherein the range of unknown audience sizes has a minimum value of a partial audience size and a maximum value of the total number of initial impressions minus a number of recorded demographic impressions plus the partial audience size.

13 . The method of claim 1 , further including:
determining the partial audience size and the number of recorded demographic impressions from the frequency distribution of the recorded demographic impressions.

14 . An apparatus, comprising:
an impression modeler to determine models, based on a total number of initial impressions and a frequency distribution of recorded demographic impressions across a partial audience size, that model the probability of obtaining the frequency distribution of the recorded demographic impressions across the partial audience for different possible unknown audience sizes of an unknown audience exposed to online media; a estimate determiner to determine an estimate a size od the unknown audience by evaluating the models for the different possible unknown audience size, across a range of unknown audience sizes.

15 . The apparatus of claim 14 , further comprising:
an audience measurement entity (AME) impressions collector to collect, for the online media, the total number of initial impression; a database proprietor (DP) impressions collector to collect the frequency distribution of recorded demographic impressions across the partial audience; an impressions allocator to allocate the total number of initial impressions among the unknown audience.

16 . (canceled)

17 . The apparatus of claim 14 , wherein the frequency distribution of the recorded demographic impressions across the partial audience is received from a database proprietor.

18 . The apparatus of claim 17 , wherein the database proprietor includes at least one of a social network service provider, a multi-service service provider, a streaming media service provider, an online shopping service provider, or a credit reporting service provider.

19 . (canceled)

20 . The apparatus of claim 14 , wherein the models are based on Beta-Binomial Distributions.

21 . (canceled)

22 . (canceled)

23 . (canceled)

24 . The apparatus of claim 14 , wherein a probability of a demographic impression being recorded for an individual is modeled as a Beta Binomial Distribution.

25 . The apparatus of claim 14 , wherein the determining of the estimate for the unknown audience size includes evaluating log-likelihood metrics for respective ones of the models using the frequency distribution of recorded demographic impressions across the partial audience, selecting one of the models based on the log-likelihood, and selecting a respective one of the possible unknown audience sizes corresponding to the selected model to be the estimate for the unknown audience size.

26 . The apparatus of claim 14 , wherein the range of unknown audience sizes has a minimum value of a partial audience size and a maximum value of the total number of initial impressions minus a number of recorded demographic impressions plus the partial audience size.

27 . (canceled)

28 . A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:
access, for an online media, a total number of initial impressions and a frequency distribution of the recorded demographic impressions across a partial audience; determine a partial audience size and a number of demographic impressions from the frequency distribution of the recorded demographic impressions; determine models, based on the total number of initial impressions and the frequency distribution of the recorded demographic impressions across the partial audience size, modeling a probability of obtaining the frequency distribution of the recorded demographic impressions across the partial audience for different possible unknown audience sizes in a range of unknown audience sizes; determine an estimate for the unknown audience size by evaluating the models for the different possible unknown audience sizes.

29 . (canceled)

30 . The storage medium as defined in claim 28 , wherein the frequency distribution of the recorded demographic impressions across the partial audience is receiv

Assignees

• Nielsen Co Us Llc

Inventors

• Sheppard Michael
• Sullivan Jonathan
• Lipa Peter
• Reid Matthew B
• Terrazas Alejandro

Classifications

• G06Q30/0246 Primary

  Traffic · CPC title