IP Library Granted Patent US 11,089,369
Granted Patent B2
US 11,089,369 · App. 16/827,272 · Granted Aug 10, 2021

Methods and apparatus to categorize media impressions by age

Inventors: Jonathan Sullivan (Hurricane, UT); Michael Sheppard (Holland, MI)
Assignee: The Nielsen Company (US), LLC
H04N21/4665H04N21/252H04N21/25883H04N21/4667
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Quick Facts
Patent No.
US 11,089,369
App. No.
16/827,272
Granted
Aug 10, 2021
Kind
B2
Abstract

Apparatus, systems, and articles of manufacture are disclosed to categorize audience members by age. An example apparatus includes memory including instructions, and a processor to execute the instructions to split audience member records from an initial node into child nodes based on comparisons of attribute-value pairs of the audience member records to a first value threshold, the attribute-value pairs representative of database subscriber activity data of audience members subscribed to a database proprietor, designate a first child node of the child nodes as a terminal node when a quantity of the audience member records of the first child node of the child nodes does not satisfy a minimum leaf size, generate an age-correction model based on the terminal node, and correct, based on the age-correction model, the age characteristic associated with the media impression, the media impression indicative of a person exposed to media presented by a media presentation device.

Claims (51)

1. An apparatus to correct a computer-assigned age characteristic associated with a media impression, the apparatus comprising:

memory; and

a processor to execute instructions to:

split audience member records in the memory from an initial node into child nodes based on comparisons of attribute-value pairs of the audience member records to a first value threshold, the attribute-value pairs of the audience member records representative of database subscriber activity data of audience members subscribed to a database proprietor;

designate a first child node of the child nodes as a terminal node when a quantity of the audience member records of the first child node of the child nodes does not satisfy a minimum leaf size;

generate a computer-generated age-correction model based on the terminal node; and

correct, based on the computer-generated age-correction model, the computer-assigned age characteristic associated with the media impression, the media impression indicative of a person exposed to media presented by a media presentation device.

2. The apparatus of claim 1 , wherein the processor is to assign a weight to the audience member records, the weight based on a quantity of audience members in a same age group as the audience member records.

3. The apparatus of claim 2 , wherein the processor is to assign the weight to the audience member records corresponding to different age groups further by:

assigning, when the quantity of audience member records grouped within one of the age groups satisfies a first threshold, a neutral weight to the audience member records in the one of the age groups;

assigning, when the quantity of the audience member records grouped within one of the age groups satisfies a second threshold, a maximum weight to the audience member records in the one of the age groups; and

when the quantity of the audience member records grouped within one of the age groups satisfies a third threshold, a proportional weight between a neutral weight and a maximum weight to the audience member records in the one of the age groups.

4. The apparatus of claim 1 , wherein the processor is to generate the audience member records based on survey data obtained from a plurality of panelists, and based on activity data corresponding to the plurality of panelists retrieved from a second database proprietor.

5. The apparatus of claim 1 , wherein the processor is to:

load, into a cache memory of the processor, a portion of the audience member records corresponding to a first one of the child nodes stored in the memory; and

compare first and second registers of the processor, the first register including a quantity of ones of the audience member records that are in the first child node, and the second register including a minimum leaf size.

6. The apparatus of claim 1 , wherein the processor is to organize the audience member records into a training set and a validation set, the training set to be stored in a first block of the memory and the validation set to be stored in a second block of the memory, the processor to apply the audience member records in the validation set to the computer-generated age-correction model to validate the computer-generated age-correction model.

7. The apparatus of claim 6 , wherein the processor is to apply the audience member records in the validation set to the computer-generated age-correction model by calculating a difference between registers containing values of an expected output of the computer-generated age-correction model and registers containing values of an actual output of the computer-generated age-correction model.

8. A non-transitory computer readable storage medium comprising machine readable instructions that, when executed, cause a processor system to at least:

split audience member records in memory from an initial node into child nodes based on comparisons of attribute-value pairs of the audience member records to a first value threshold, the attribute-value pairs of the audience member records representative of database subscriber activity data of audience members subscribed to a database proprietor;

designate a first child node of the child nodes as a terminal node when a quantity of the audience member records of the first child node of the child nodes does not satisfy a minimum leaf size;

generate a computer-generated age-correction model based on the terminal node; and

correct, based on the computer-generated age-correction model, a computer-assigned age characteristic associated with a media impression, the media impression indicative of a person exposed to media presented by a media presentation device.

9. The non-transitory computer readable storage medium of claim 8 , further including instructions that, when executed, cause the processor system to assign a weight to the audience member records, the weight based on a quantity of audience members in a same age group as the audience member records.

10. The non-transitory computer readable storage medium of claim 9 , further including instructions that, when executed, cause the processor system to assign the weight to the audience member records corresponding to different age groups further by:

assigning, when the quantity of audience member records grouped within one of the age groups satisfies a first threshold, a neutral weight to the audience member records in the one of the age groups;

assigning, when the quantity of the audience member records grouped within one of the age groups satisfies a second threshold, a maximum weight to the audience member records in the one of the age groups; and

when the quantity of the audience member records grouped within one of the age groups satisfies a third threshold, a proportional weight between a neutral weight and a maximum weight to the audience member records in the one of the age groups.

11. The non-transitory computer readable storage medium of claim 8 , further including instructions that, when executed, cause the processor system to generate the audience member records based on survey data obtained from a plurality of panelists, and based on activity data corresponding to the plurality of panelists retrieved from a second database proprietor.

12. The non-transitory computer readable storage medium of claim 8 , further including instructions that, when executed, cause the processor system to:

load, into a cache memory of the processor system, a portion of the audience member records corresponding to a first one of the child nodes stored in the memory; and

compare first and second registers of the processor system, the first register including a quantity of ones of the audience member records that are in the first child node, and the second register including a minimum leaf size.

13. The non-transitory computer readable storage medium of claim 8 , further including instructions that, when executed, cause the processor system to organize the audience member records into a training set and a validation set, the training set to be stored in a first block of memory and the validation set to be stored in a second block of the memory, the processor system to apply the audience member records in the validation set to the computer-generated age-correction model to validate the computer-generated age-correction model.

14. The non-transitory computer readable storage medium of claim 13 , further including instructions that, when executed, cause the processor system to apply the audience member records in the validation set to the computer-generated age-correction model by calculating a difference between registers containing values of an expected output of the computer-generated age-correction model and registers containing values of an actual output of the computer-generated age-correction model.

15. A method comprising:

splitting, by executing an instruction with at least one processor, audience member records in computer memory from an initial node into child nodes based on comparisons of attribute-value pairs of the audience member records to a first value threshold, the attribute-value pairs of the audience member records representative of database subscriber activity data of audience members subscribed to a database proprietor;

designating, by executing an instruction with the at least one processor, a first child node of the child nodes as a terminal node when a quantity of the audience member records of the first child node of the child nodes does not satisfy a minimum leaf size;

generating, by executing an instruction with the at least one processor, a computer-generated age-correction model based on the terminal node; and

correcting, by executing an instruction with the at least one processor, based on the computer-generated age-correction model, a computer-assigned age characteristic associated with a media impression, the media impression indicative of a person exposed to media presented by a media presentation device.

16. The method of claim 15 , further including assigning a weight to the audience member records, the weight based on a quantity of audience members in a same age group as the audience member records.

17. The method of claim 16 , further including assigning the weight to the audience member records corresponding to different age groups further by:

assigning, when the quantity of audience member records grouped within one of the age groups satisfies a first threshold, a neutral weight to the audience member records in the one of the age groups;

assigning, when the quantity of the audience member records grouped within one of the age groups satisfies a second threshold, a maximum weight to the audience member records in the one of the age groups; and

assigning, when the quantity of the audience member records grouped within one of the age groups satisfies a third threshold, a proportional weight between a neutral weight and a maximum weight to the audience member records in the one of the age groups.

18. The method of claim 15 , further including generating the audience member records based on survey data obtained from a plurality of panelists, and based on activity data corresponding to the plurality of panelists retrieved from a second database proprietor.

19. The method of claim 15 , further including:

loading, into a cache memory, a portion of the audience member records corresponding to a first one of the child nodes stored in the memory; and

comparing first and second registers, the first register including a quantity of ones of the audience member records that are in the first child node, and the second register including a minimum leaf size.

20. The method of claim 15 , further including:

organizing the audience member records into a training set and a validation set, the training set to be stored in a first block of memory and the validation set to be stored in a second block of the memory; and

applying the audience member records in the validation set to the computer-generated age-correction model to validate the computer-generated age-correction model.

Assignments (8)
RELEASE (REEL 054066 / FRAME 0064) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063605/0001 →
RELEASE (REEL 053473 / FRAME 0001) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063603/0001 →
SECURITY INTEREST Recorded May 8, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: ARES CAPITAL CORPORATION
Reel/Frame 063574/0632 →
SECURITY INTEREST Recorded Apr 28, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: CITIBANK, N.A.
Reel/Frame 063561/0381 →
SECURITY AGREEMENT Recorded Jan 31, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 063560/0547 →
CORRECTIVE ASSIGNMENT TO CORRECT THE PATENTS LISTED ON SCHEDULE 1 RECORDED ON 6-9-2020 PREVIOUSLY RECORDED ON REEL 053473 FRAME 0001. ASSIGNOR(S) HEREBY CONFIRMS THE SUPPLEMENTAL IP SECURITY AGREEMENT. Recorded Oct 7, 2020
From: A.C. NIELSEN (ARGENTINA) S.A.; A.C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A
Reel/Frame 054066/0064 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Jun 9, 2020
From: A. C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NIELSEN UK FINANCE I, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A.
Reel/Frame 053473/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 19, 2020
From: SULLIVAN, JONATHAN; SHEPPARD, MICHAEL
To: THE NIELSEN COMPANY (US), LLC
Reel/Frame 052695/0833 →
Continuity (4)
Continuation 16239954 · Jan 4, 2019
Continuation 15669406 · Aug 4, 2017
Continuation 14928468 · Oct 30, 2015
Related Publication 20200221178A1 · Jul 9, 2020