Confidence Factor Filtering for IT System Reliability
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Solution Overview
Problem
Current systems for forming IT systems, such as business systems, face challenges in ensuring the accuracy and reliability of resources and relationships recorded in databases, as they often include resources with low confidence factors, which can impact system performance and reliability.
Innovation Solution
A method and system that utilize confidence factors to filter resources and relationships, only incorporating those with confidence levels equal to or greater than a tolerable threshold, thereby forming a system with higher accuracy and reliability by prioritizing and visualizing resources and relationships based on their confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all resources and relationships are included in the system regardless of confidence level, then the system comprehensiveness is improved, but the system reliability deteriorates
Solution Approach 1:
The patent applies local quality by assigning different confidence levels to different resources and relationships within the system. Each resource is evaluated individually and assigned a confidence factor based on its specific characteristics, allowing the system to treat each component according to its own quality level rather than applying a uniform standard. This enables the system to maintain comprehensiveness while ensuring reliability through localized quality assessment and filtering.
Solution Approach 2:
The patent changes the parameter of confidence level by introducing confidence factors as a quantitative measure for each resource. By adjusting the threshold parameter for acceptable confidence levels, the system can dynamically control which resources are included. This parameter change allows flexible balancing between comprehensiveness and reliability based on specific system requirements and tolerance levels.
2Measurement precision
If resources with low confidence factors are excluded from the system, then the system accuracy is improved, but the system completeness worsens
Solution Approach 1:
The patent applies dynamics by making the system configuration adjustable through configurable tolerance thresholds. The threshold for excluding low-confidence resources is not fixed but can be dynamically adjusted based on system needs. This allows the system to adapt between accuracy and completeness by changing the threshold parameter, enabling flexible optimization for different operational contexts without compromising either attribute permanently.
3Reliability
If a tolerable confidence factor threshold is applied to filter resources, then the system reliability is improved, but the system complexity increases
Solution Approach 1:
The patent applies self-service by implementing automatic confidence factor calculation and threshold-based filtering without requiring manual intervention. The system autonomously evaluates each resource, calculates its confidence factor, and determines whether to include it based on the configured threshold. This automated self-service approach maintains reliability through consistent filtering while minimizing the complexity burden on operators, as the system performs the complex evaluation tasks automatically.
Data Source
AI summary
A method for using confidence factors in forming a system may include receiving a tolerable confidence factor. The method may also include utilizing only resources and relationships of a plurality of resources and relationships with confidence factors equal to or greater than the tolerable confidence factor to form the system.