Rule Evaluation Weighted Element Ordering
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Solution Overview
Problem
Existing systems for evaluating rules in complex computer systems are inefficient as they require retrieving and evaluating multiple characteristic values, leading to suboptimal performance when determining which accounts meet complex rules.
Innovation Solution
A system and method that weights elements in a rule based on their influence and likelihood of determining the rule's outcome, allowing for early evaluation termination if the rule is not applicable, and prioritizes the retrieval of characteristic values corresponding to the most dispositive factors first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all characteristic values are retrieved and evaluated to determine rule applicability, then complete accuracy is achieved, but the number of lookups and processing time increase
Solution Approach 1:
The system performs preliminary actions by retrieving and evaluating characteristic values in a weighted order before complete rule evaluation is needed. High-weight characteristics are retrieved first based on their likelihood of determining rule applicability, allowing early termination of the evaluation process when the outcome becomes determined, thus reducing overall lookup time while maintaining accuracy.
Solution Approach 2:
The system applies partial action by retrieving only the necessary subset of characteristic values required to determine rule applicability rather than all possible values. By using weighted probabilities to identify which characteristics are most likely to be dispositive, the system retrieves fewer values on average while still achieving complete and accurate rule evaluation.
2Reliability
If multiple characteristic values are retrieved for complex rules, then complete evaluation is possible, but the number of lookups increases
Solution Approach 1:
The system performs preliminary retrieval of characteristic values ordered by their weighted probabilities of being dispositive. This preliminary action allows the evaluation to proceed efficiently by having the most likely determining characteristics ready first, enabling early termination when the rule outcome is determined, thus improving productivity without sacrificing reliability.
Solution Approach 2:
The system changes the parameter of retrieval order by assigning weights to characteristics based on their likelihood of determining rule applicability. This parameter change optimizes the sequence in which characteristics are retrieved, allowing the system to achieve complete and reliable evaluation with fewer average lookups by prioritizing the most informative characteristics.
3Ease of manufacture
If characteristic values are retrieved in arbitrary order, then implementation is simple, but the average number of lookups increases
Solution Approach 1:
The system changes the parameter of retrieval order from arbitrary to weighted-based ordering. By assigning weights to characteristics according to their likelihood of being dispositive and retrieving them in descending weight order, the system significantly improves lookup efficiency. The implementation remains relatively simple by using pre-calculated weights and a straightforward sorting mechanism.
Solution Approach 2:
The system performs preliminary calculation and assignment of weights to characteristics before the actual rule evaluation process. This preliminary action establishes an optimal retrieval order that improves productivity, while the actual implementation during rule evaluation remains simple by just following the pre-determined weighted sequence.
Data Source
AI summary
A system and method reduces or minimizes the number of characteristic values required to evaluate a rule by selecting elements of the rule in an order most likely to allow evaluation of the rule without requiring evaluation of other elements of the rule. The selection may be a function of one or both of the structure of the rule and the probability that an element will resolve to a particular value of true or false.