Dynamic Query Aggregation via Hierarchical Matrix Traversal
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Solution Overview
Problem
Existing systems face challenges in efficiently managing and sharing large amounts of data across multiple computing systems and applications, particularly in ensuring data accuracy and consistency.
Innovation Solution
A system that utilizes a non-transitory machine-readable medium to store a program that receives requests for questions associated with a location and category, identifies hierarchies of locations and categories, and generates an aggregate collection of questions by traversing a two-dimensional matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large number of computing devices are used to create and store data, then the quantity of data increases, but the complexity of managing and ensuring data accuracy increases
Solution Approach 1:
The patent segments data management by organizing data into hierarchical structures (parent-child relationships) and categorizing it into different data types. This segmentation allows the system to manage large quantities of data by breaking them down into manageable units that can be processed and validated individually, reducing the overall complexity of data management.
Solution Approach 2:
The patent introduces an intermediary system that acts as a mediator between multiple computing devices and the central data management system. This intermediary handles data validation, enrichment, and relationship mapping, reducing the burden on individual devices and simplifying the overall data management complexity while handling large data quantities.
2Adaptability or versatility
If data is shared across multiple systems and applications, then the versatility of data usage increases, but the difficulty of ensuring data accuracy and consistency increases
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously validates data accuracy, checks for consistency across different systems and applications, and provides enrichment based on identified gaps. This feedback loop ensures that data remains accurate and consistent even as it is shared and used across multiple platforms, maintaining reliability while enabling versatile data usage.
Solution Approach 2:
The patent creates a universal data structure and validation framework that can be applied across multiple systems and applications. By establishing common data models, hierarchical relationships, and validation rules that work universally, the system enables data to be shared and used across different platforms while maintaining accuracy and consistency through the standardized approach.
3Reliability
If the system validates data accuracy across hierarchical structures, then the reliability of data increases, but the time required for validation increases
Solution Approach 1:
The patent performs preliminary validation actions by establishing hierarchical relationships and data type classifications before full validation occurs. By pre-organizing data into structured hierarchies and identifying data types in advance, the system reduces the time required for comprehensive validation while maintaining high data accuracy, as the preliminary structure guides the validation process.
Solution Approach 2:
The patent applies partial validation actions by focusing validation efforts on critical data elements and hierarchical relationships that have the greatest impact on data accuracy. Rather than validating every single data point equally, the system performs targeted validation on key elements, reducing overall validation time while maintaining sufficient data reliability for business operations.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a request for questions associated with a location and a category. The program also identifies a matrix, a hierarchy of locations associated with the matrix, and a hierarchy of categories associated with the matrix. The program further determines an aggregate collection of questions from a plurality of sets of questions based on the matrix, the hierarchy of locations, and the hierarchy of categories. The program also generates the aggregate collection of questions.