Attribute Value Derivation in Hierarchical Data Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Hierarchical data models require efficient methods to derive and display data without imposing significant computational burdens, as retrieving data from these structures can be time-consuming and compute-intensive.
Innovation Solution
The method involves using attribute value derivation functions defined in an attribute value derivation header to derive target attribute values from source attributes in a hierarchical data model, incorporating inheritance logic and user interfaces for data manipulation and filtering, thereby reducing manual effort and enhancing usability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is retrieved by traversing the entire hierarchical tree from the root node, then complete data can be obtained, but the process becomes compute intensive and time consuming
Solution Approach 1:
The system pre-computes and stores derived attribute values in the hierarchical data model before they are needed. When data is retrieved, these pre-computed values are directly returned without requiring traversal of the entire tree or re-computation, thus maintaining data completeness while dramatically reducing retrieval time
Solution Approach 2:
The patent extracts only the necessary data portions from the hierarchical tree based on user preferences and requirements, rather than retrieving the entire tree. This selective extraction approach maintains data completeness for needed information while avoiding the computational burden of processing unnecessary data
2Manufacturing precision
If manual mapping and derivation of attribute values is performed, then data accuracy can be maintained, but significant manual maintenance effort is required
Solution Approach 1:
The system implements automated attribute value derivation functions that self-compute derived attribute values from source attributes using predefined relationships and rules. This self-service mechanism maintains data accuracy through consistent application of derivation logic while eliminating the need for manual mapping and maintenance of attribute relationships
Solution Approach 2:
The patent creates a universal attribute value derivation framework that can handle multiple types of attribute relationships and derivation scenarios through a single automated system. This multi-functional approach maintains data accuracy across diverse data types while reducing manual maintenance effort by providing a unified solution for all derivation needs
Data Source
AI summary
A system, a method, and a computer program product for deriving target attribute values based on source attributes defined by a hierarchical data mode are disclosed. An attribute value derivation function to change a target attribute data value corresponding to a source attribute stored in a hierarchical data model and an instruction corresponding to the source attribute are provided. The attribute value derivation function is defined by an attribute value derivation header containing metadata describing hierarchical data model and an attribute value derivation instruction for deriving the target attribute based on the source attribute. Using the attribute value derivation function, a target attribute data value is derived. A user interface is generated to display the derived target attribute data value.