Cardinality Models for Privacy-Sensitive Reach Assessment
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Solution Overview
Problem
Existing systems lack the capability to perform a privacy-sensitive assessment of digital component transmission reach, making it difficult to determine the number of users who received digital components while preserving individual user privacy and efficiently managing resource allocation.
Innovation Solution
A system implemented on computers that uses a cardinality model with sparse matrix parameters to determine the number of users included in a target group by generating an alternative representation of set expressions in terms of primitive sets and subset unions, allowing for privacy-sensitive assessment of digital component transmission reach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional user tracking methods are used to determine transmission reach, then accurate measurement of user count is achieved, but user privacy is compromised
Solution Approach 1:
The patent introduces a cardinality model as an intermediary mathematical framework that operates on aggregated user set data without accessing individual user information. The model uses set theory and linear algebra to compute transmission reach through cardinality calculations on user sets, publishers, and time windows, thereby achieving accurate measurement while preserving user privacy through mathematical abstraction rather than direct user-level tracking
Solution Approach 2:
The patent transforms the measurement approach by changing from individual user-level parameters to aggregated set-based parameters. Instead of tracking individual users, the system uses cardinalities of user sets, publisher sets, and time window sets as parameters in the cardinality model equations, enabling reach calculation through parameter transformation that eliminates direct user identification while maintaining measurement accuracy
2Measurement precision
If detailed user tracking data is collected to assess transmission reach, then accurate reach determination is achieved, but system resource consumption increases
Solution Approach 1:
The patent extracts only the essential aggregated data needed for reach calculation - specifically, the cardinalities of user sets, publisher sets, and time window sets - while discarding unnecessary individual user tracking data. This extraction approach allows the system to perform accurate reach assessment using minimal data processing, reducing computational resource consumption while maintaining measurement precision through the cardinality model's efficient mathematical operations
Data Source
AI summary
In one aspect, there is provided a method performed by one or more computers for privacy-sensitive assessment of digital component transmission reach based on cardinalities of subset unions of a collection of user sets, the method including: receiving a request to determine a number of users that are included in a target group of users that received at least one transmission of a digital component, where the request includes a set expression defined in terms of the collection of user sets, generating an alternative representation of the set expression in terms of primitive sets, applying a cardinality model to each primitive to generate a cardinality of each primitive set as a linear combination of cardinalities of subset unions of the collection of user sets, and determining the number of users included in the target group of users based on the cardinalities of the primitive sets.