Processor systems to estimate audience sizes and impression counts for different frequency intervals
Abstract
Processor systems to estimate audience sizes and impression counts for different frequency intervals are disclosed. An example processor system includes a memory management unit (MMU) to assign requests from computing devices indicative of accesses to media to a first block of memory, a total count of the requests corresponding to a total number of census impressions. The MMU to assign user-identified impression data corresponding to user-identified impressions to a second block of memory, the user-identified impressions associated with user-identified individuals for whom first demographic information is stored by a database proprietor. The processor system including an arithmetic logic unit (ALU) to determine multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for the census impressions, and to determine a plurality of census impression counts associated with the census impressions based on the multipliers, different ones of the census impression counts corresponding to different ones of impression frequency intervals.
Claims
exact text as granted — not AI-modified1 . A processor system, comprising:
memory; a memory management unit (MMU) to:
assign requests from computing devices indicative of accesses to media at the computing devices to a first block of the memory, a total count of the requests corresponding to a total number of census impressions associated with the media, a first portion of the census impressions corresponding to user-identified impressions and a second portion of the census impressions corresponding to unidentified impressions; and
assign user-identified impression data corresponding to the user-identified impressions to a second block of the memory, the user-identified impressions associated with user-identified individuals for whom first demographic information is stored by a database proprietor, the user-identified impression data including a plurality of user-identified impression counts associated with a corresponding plurality of impression frequency intervals; and
an arithmetic logic unit (ALU) to:
determine multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for the census impressions, the multipliers based on census constraints defined by the total number of census impressions; and
determine a plurality of census impression counts associated with the census impressions based on the multipliers, different ones of the census impression counts corresponding to different ones of the impression frequency intervals.
2 . The processor system of claim 1 , wherein at least two of the user-identified impression counts correspond to a single one of the impression frequency intervals, different ones of the at least two of the user-identified impression counts corresponding to audience members associated with different demographics, the ALU to determine different ones of the plurality of census impressions according to the different demographics.
3 . The processor system of claim 1 , wherein the ALU is to determine the first probability distribution by identifying a distribution that satisfies the principle of maximum entropy with respect to the user-identified impressions subject to user-identified constraints defined by the user-identified impression data.
4 . The processor system of claim 3 , wherein the ALU is to determine the first probability distribution without directly calculating individual probabilities within the first probability distribution.
5 . The processor system of claim 1 , wherein the MMU is to store user-identified audience size data including different ones of a plurality of first unique audience sizes associated with different ones of the plurality of user-identified impression counts, the ALU to determine, based on the multipliers, a plurality of second unique audience sizes corresponding to audience members associated with the census impression counts, different ones of the plurality of second unique audience sizes corresponding to different ones of the plurality of impression frequency intervals.
6 . The processor system of claim 1 , wherein the multipliers are Lagrange multipliers.
7 . The processor system of claim 1 , wherein the census constraints include a total universe estimate corresponding to a number of people within a geographic region of interest capable of accessing the media.
8 . A non-transitory computer readable medium comprising instructions that, when executed, cause a processor to at least:
assign requests from computing devices indicative of accesses to media at the computing devices to a first block of memory, a total count of the requests corresponding to a total number of census impressions associated with the media, a first portion of the census impressions corresponding to user-identified impressions and a second portion of the census impressions corresponding to unidentified impressions; and assign user-identified impression data corresponding to the user-identified impressions to a second block of the memory, the user-identified impressions associated with user-identified individuals for whom first demographic information is stored by a database proprietor, the user-identified impression data including a plurality of user-identified impression counts associated with a corresponding plurality of impression frequency intervals; and determine multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for the census impressions, the multipliers based on census constraints defined by the total number of census impressions; and determine a plurality of census impression counts associated with the census impressions based on the multipliers, different ones of the census impression counts corresponding to different ones of the impression frequency intervals.
9 . The non-transitory computer readable medium of claim 8 , wherein at least two of the user-identified impression counts correspond to a single one of the impression frequency intervals, different ones of the at least two of the user-identified impression counts corresponding to audience members associated with different demographics, the instructions further causing the processor to determine different ones of the plurality of census impressions according to the different demographics.
10 . The non-transitory computer readable medium of claim 8 , wherein the instructions further cause the processor to determine the first probability distribution by identifying a distribution that satisfies the principle of maximum entropy with respect to the user-identified impressions subject to user-identified constraints defined by the user-identified impression data.
11 . The non-transitory computer readable medium of claim 10 , wherein the instructions further cause the processor to determine the first probability distribution without directly calculating individual probabilities within the first probability distribution.
12 . The non-transitory computer readable medium of claim 8 , wherein the instructions further cause the processor to:
store user-identified audience size data including different ones of a plurality of first unique audience sizes associated with different ones of the plurality of user-identified impression counts; and determine, based on the multipliers, a plurality of second unique audience sizes corresponding to audience members associated with the census impression counts, different ones of the plurality of second unique audience sizes corresponding to different ones of the plurality of impression frequency intervals.
13 . The non-transitory computer readable medium of claim 8 , wherein the multipliers are Lagrange multipliers.
14 . The non-transitory computer readable medium of claim 8 , wherein the census constraints include a total universe estimate corresponding to a number of people within a geographic region of interest capable of accessing the media.
15 . A method, comprising:
assigning requests from computing devices indicative of accesses to media at the computing devices to a first block of memory, a total count of the requests corresponding to a total number of census impressions associated with the media, a first portion of the census impressions corresponding to user-identified impressions and a second portion of the census impressions corresponding to unidentified impressions; and assigning user-identified impression data corresponding to the user-identified impressions to a second block of the memory, the user-identified impressions associated with user-identified individuals for whom first demographic information is stored by a database proprietor, the user-identified impression data including a plurality of user-identified impression counts associated with a corresponding plurality of impression frequency intervals; and determining multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for the census impressions, the multipliers based on census constraints defined by the total number of census impressions; and determining a plurality of census impression counts associated with the census impressions based on the multipliers, different ones of the census impression counts corresponding to different ones of the impression frequency intervals.
16 . The method of claim 15 , wherein at least two of the user-identified impression counts correspond to a single one of the impression frequency intervals, different ones of the at least two of the user-identified impression counts corresponding to audience members associated with different demographics, the method further including determining different ones of the plurality of census impressions according to the different demographics.
17 . The method of claim 15 , further including determining the first probability distribution by identifying a distribution that satisfies the principle of maximum entropy with respect to the user-identified impressions subject to user-identified constraints defined by the user-identified impression data.
18 . The method of claim 17 , further including determining the first probability distribution without directly calculating individual probabilities within the first probability distribution.
19 . The method of claim 15 , further including:
storing user-identified audience size data including different ones of a plurality of first unique audience sizes associated with different ones of the plurality of user-identified impression counts; and determining, based on the multipliers, a plurality of second unique audience sizes corresponding to audience members associated with the census impression counts, different ones of the plurality of second unique audience sizes corresponding to different ones of the plurality of impression frequency intervals.
20 . The method of claim 15 , wherein the multipliers are Lagrange multipliers.Join the waitlist — get patent alerts
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