Dynamic Data Association Rules for Efficient Retrieval
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Solution Overview
Problem
Conventional databases store and retrieve data using rigid one-to-one relationships, which are time-consuming and costly.
Innovation Solution
Implement data associations by abstracting one-to-one relationships into broader linkages using an associations rules engine, updating metadata catalogs with these associations, and utilizing data aggregation services to enhance data virtualization and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional databases use rigid one-to-one relationships between data objects, then data structure integrity is maintained, but data storage and retrieval become time-consuming and costly
Solution Approach 1:
The patent segments the rigid one-to-one relationship structure into multiple independent association rules that can be evaluated separately. Each association rule represents a potential relationship between data objects, and the system evaluates multiple rules in parallel to determine actual associations, thereby maintaining structural integrity while improving retrieval efficiency
Solution Approach 2:
The patent introduces dynamic association rules that can adaptively determine relationships between data objects based on evaluated conditions. Instead of fixed rigid relationships, the system dynamically evaluates association rules with different conditions and weights to establish flexible data associations, improving both efficiency and adaptability
2Loss of information
If conventional databases store detailed one-to-one relationships between all data object pairs, then complete relationship information is preserved, but storage cost and processing time increase
Solution Approach 1:
The patent extracts only the essential association conditions and weights from complete one-to-one relationship definitions. Instead of storing and processing all possible relationship details, the system extracts key association rules with their evaluation conditions, thereby preserving necessary relationship information while significantly reducing storage and processing requirements
Solution Approach 2:
The patent evaluates association rules partially by selectively applying evaluation conditions rather than processing complete relationship definitions. The system uses weighted condition matching to determine associations without requiring full relationship information, achieving efficient processing while maintaining sufficient relationship completeness for practical purposes
Data Source
AI summary
Novel tools and techniques are provided for implementing data storage and/or retrieval, and, more particularly, for implementing data associations. In various embodiments, an associations rules engine might query data aggregation data services to determine whether a first data object (which along with a first relationship rule that indicates a one-to-one relationship between the first data object and a corresponding second data object) is associated with one or more third data objects; might abstract the first data object, the first relationship rule, and the one or more third data objects; might update, in a metadata catalog, a catalog entry corresponding to the first data object with one or more associations among various data objects; and might provide a requesting computing system with access to the catalog entry corresponding to the first data object, the computing system performing one or more computational tasks using the associations stored in the catalog entry.