Behavior-Based Re-Prompt for Media Metering Accuracy
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Solution Overview
Problem
Current media consumption monitoring systems face inaccuracies due to burdensome registration processes and inadequate authentication frequency, leading to incorrect attribution of media consumption to the correct user, causing user frustration and reduced measurement accuracy.
Innovation Solution
A system that includes a data store, processor, registration module, behavior learning unit, behavior determination unit, and re-prompt determination unit to request authentication based on learned user behavior and predetermined thresholds, ensuring accurate user identification by periodically prompting users when significant behavior changes are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the measurement system requires each media consumer to register themselves, then the accuracy of media consumption attribution is improved, but the ease of operation deteriorates due to the burdensome registration process
Solution Approach 1:
The system automatically detects and learns media consumer behavior patterns without requiring manual registration. The behavior learning unit continuously monitors consumption habits and the behavior determination unit automatically identifies when re-prompting is needed, eliminating the burdensome manual registration process while maintaining accurate attribution.
Solution Approach 2:
The system implements a feedback loop where the behavior learning unit continuously monitors media consumer behavior, the behavior determination unit compares current behavior against learned patterns, and the re-prompt determination unit adjusts authentication frequency accordingly. This closed-loop feedback mechanism maintains accuracy without requiring repeated manual registration.
2Measurement precision
If the measurement system periodically requests authentication frequently, then the accuracy of media consumption attribution is improved, but the ease of operation deteriorates due to user perturbation from excessive requests
Solution Approach 1:
The system dynamically adjusts the authentication prompt frequency based on detected behavior changes. The behavior determination unit continuously monitors for significant deviations from learned behavior patterns and only triggers re-prompting when such changes are detected, rather than using a fixed frequent scheduling approach. This dynamic adjustment maintains accuracy while minimizing user perturbation.
Solution Approach 2:
The system changes the parameter of authentication frequency from a static high-frequency approach to a dynamic parameter that adapts based on behavior analysis. The re-prompt determination unit adjusts the timing and frequency of authentication requests based on real-time behavior comparison, optimizing the balance between accuracy maintenance and user experience.
Data Source
AI summary
A system for determining to request a re-prompt for a metering device, includes: a data store including a computer readable medium storing a program of instructions for determining to request the re-prompt; a processor that executes the program of instructions; a registration module to register a media consumer associated with the metering device; a behavior learning unit to learn a behavior associated with the registered media consumer; a behavior determination unit to determine a difference between the behavior associated with the registered media consumer and a behavior associated with a present media consumer; and a re-prompt determination unit to request the re-prompt to the metering device based on the difference being greater than a predetermined threshold.