Blockchain Prediction Mechanism for User Action Incentives
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Solution Overview
Problem
Existing systems struggle to accurately predict whether a user will perform certain operations, such as two-factor authentication or sign-ups, leading to inefficient resource allocation and user experience issues.
Innovation Solution
A prediction system leveraging blockchain technology to analyze user behavior data using machine learning models, generating predictions based on past operations recorded on a blockchain, and deploying executable program code to incentivize desired actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prediction systems are used to predict user operations, then resource allocation can be performed, but prediction accuracy is insufficient leading to inefficient resource allocation
Solution Approach 1:
The system performs preliminary actions by deploying executable program code to the blockchain in advance that automatically executes when prediction criteria are met. This allows the system to proactively prepare incentive mechanisms before user actions occur, improving both prediction accuracy and resource allocation efficiency by having predetermined responses ready based on analyzed user behavior patterns.
Solution Approach 2:
The system implements feedback by continuously monitoring user operations on the blockchain, comparing actual behavior against predicted behavior, and using this information to refine prediction models. The executable code on the blockchain provides automated feedback loops where prediction outcomes trigger specific actions, and results of those actions feed back into improving future predictions, thereby enhancing both accuracy and resource allocation.
2Ease of operation
If executable program code is deployed to blockchain to incentivize user actions, then user satisfaction improves through personalized incentives, but system complexity increases
Solution Approach 1:
The system applies self-service by enabling the blockchain-based executable code to automatically manage incentive distribution without requiring manual intervention. The code autonomously monitors user actions, evaluates prediction criteria, and dispenses incentives based on predetermined rules, thereby improving user satisfaction through personalized automated incentives while avoiding the complexity of manual incentive management systems.
Solution Approach 2:
The patent implements universality by designing a multi-functional executable code structure that can handle multiple prediction criteria, various incentive types, and different user behavior patterns within a single unified framework. This universal approach allows the system to provide personalized incentives across diverse scenarios without creating separate complex systems for each case, thus improving user satisfaction while controlling overall system complexity.
Data Source
AI summary
Techniques are disclosed pertaining to generating a prediction as to whether a user will perform certain operations. A computer system may deploy, to a set of blockchains, program code that is executable to perform an operation of a first operation type in response to the user performing an operation of a second operation type with respect to a web service system. The computer system can receive, from the web service system, a request to generate a prediction as to whether the user will interact with the web service system to perform a set of operations of the second operation type. The computer system may access operation history information, from the set of blockchains, pertaining to the user that identifies a set of previous operations performed by the user. The computer system generates the prediction based on the operation history information and provides the prediction to the web service system.