Third-Party Media Interaction Verification via Event Heuristics
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Solution Overview
Problem
Existing computing devices struggle to accurately determine user engagement with third-party content, leading to false positives and false negatives in rewarding interactions, which results in resource wastage and user frustration.
Innovation Solution
A client system detects interaction events during the presentation of third-party media streams and transmits these events to a remote host server, where an interaction heuristic is applied to estimate the likelihood of user engagement, allowing the application to provide rewards based on this likelihood.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the application assumes user interaction with third-party content without verification, then the reward can be provided quickly, but false positives occur leading to resource wastage and user frustration
Solution Approach 1:
The patent introduces an intermediary verification system that captures interaction events from the third-party content player and transmits them to the application. This mediator (the event capture and transmission mechanism) allows the application to reliably verify actual user interactions without directly accessing the player's internal state, thus resolving the contradiction between quick reward provision and accurate interaction detection.
Solution Approach 2:
The system implements feedback by capturing interaction events during content playback and transmitting this information back to the application. This feedback loop enables the application to make informed decisions about reward provision based on actual user behavior, eliminating false positives while maintaining efficient reward delivery when interactions are confirmed.
2Reliability
If the application verifies user interaction with third-party content, then false positives are reduced, but additional bandwidth and processor consumption occur
Solution Approach 1:
The verification system operates autonomously by automatically capturing interaction events during content playback and transmitting them to the application without requiring additional manual verification steps. This self-service approach reduces the need for extra processor-intensive verification routines and minimizes bandwidth consumption by utilizing existing event data streams.
Solution Approach 2:
Interaction events are captured and transmitted in advance during the content playback itself, before the application needs to make reward decisions. This preliminary action ensures that verification data is already available when needed, eliminating the need for additional verification processing and reducing overall system resource consumption.
3Loss of energy
If the application does not verify user interaction, then resource consumption is minimized, but false negatives occur causing user frustration
Solution Approach 1:
The intermediary event capture system provides a low-overhead verification mechanism that automatically tracks user interactions during content playback. This mediator enables reliable detection of genuine interactions (reducing false negatives) while maintaining minimal resource consumption by utilizing existing player event streams rather than implementing complex verification protocols.
Data Source
AI summary
A client system presents, within an execution environment of an application, a third-party media stream distinct from the application, received from a remote host server via a network. The client system detects interaction events during presentation of the third-party media stream, and transmits descriptions of the detected interaction events to the remote host server. The client system updates a data set with data corresponding to detected interaction events and generates, by application of an interaction heuristic to the data set, an interaction score indicative of a likelihood of engagement with the third-party media stream. The interaction score is provided to the application, which may then provide a reward based on the likelihood of engagement. In some implementations, the interaction heuristic is based on a number or frequency of interaction events, e.g., button utilization, screen taps, device motion, or screen changes detected during presentation of the received third-party media stream.