Recipient Profile Prediction for Data Transfer Accuracy
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Solution Overview
Problem
Errors in directing data transfers in computer networks often result in incorrect recipients being targeted, leading to unnecessary resource consumption, unintended consequences, and delays in correcting these errors.
Innovation Solution
A computerized data transfer system that includes a data store of sender-specific recipients, a master participant data store, and a data transfer history store, which generates a predicted transfer profile for each recipient to identify deviations and update the recipient list, ensuring accurate recipient selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sender manually selects recipient from list, then ease of operation is improved, but reliability deteriorates due to outdated or incorrect addressing particulars
Solution Approach 1:
The system implements feedback by continuously monitoring data transfer outcomes and using this information to update recipient profiles. When a data transfer is completed or fails, the system learns from this feedback and automatically updates the addressing particulars in the recipient profile, ensuring the list remains current without requiring manual intervention.
Solution Approach 2:
The system performs self-service by automatically maintaining and updating recipient profiles using historical data transfer information. The sender device autonomously retrieves and processes data transfer history to keep addressing particulars current, eliminating the need for manual updates while maintaining high reliability.
2Reliability
If system monitors and updates recipient profiles using historical data, then reliability is improved, but device complexity increases
Solution Approach 1:
The sender device performs multiple functions: it serves as both the interface for initiating data transfers and the system for monitoring and updating recipient profiles. By combining these functions in a single device, the system avoids the complexity of separate monitoring systems while maintaining reliability through integrated historical data analysis.
3Productivity
If system generates predicted transfer profiles based on past transfers, then productivity is improved by preventing errors, but use of energy increases due to continuous data processing
Solution Approach 1:
The system performs preliminary action by generating predicted transfer profiles in advance based on historical data, so that when a new data transfer is initiated, the system can quickly compare and validate the recipient information. This prevents errors before they occur, improving productivity while the energy cost is amortized over time through proactive profile maintenance.
Data Source
AI summary
A computerized data transfer system allows data transfers to be initiated over a network between senders and recipients. Individual senders initiate data transfers over the network by selecting a recipient from a list at a sender device. The system includes a data store of sender specific recipients, a data transfer history data store of past transfers; and a master participant data store storing profiles of recipients for which transfers can be initiated. The system includes a computing device that for selected senders, retrieves entries of the data store of sender specific recipients, master participant data store and data transfer history data store; generates a predicted transfer profile for each recipient for the sender, based on past data transfers and the master participant data store to identify deviations therefrom; and updates the data store of sender specific recipients for the selected sender to update entries for recipients associated with identified deviations.