Object Categorization via Bidirectional Mapping Convergence
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Solution Overview
Problem
The challenge lies in categorizing objects across computer systems with different architectures, where existing solutions fail to provide an automatic and consistent mapping due to varying category hierarchies, leading to inconsistencies and the need for user interaction.
Innovation Solution
A method is introduced that involves assigning objects to recipient categories using predefined mappings, with a rule-based reassignment algorithm to ensure convergence, allowing for automatic categorization without user input by determining object-specific categories and handling assignments at different hierarchy levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If 1×N directed key mappings are used for categorization, then mapping process is simplified, but automatic categorization without user interaction is not achieved
Solution Approach 1:
The system applies bidirectional mappings (first mapping from sender to recipient categories, second mapping from recipient back to sender categories) and verifies convergence between the two mappings. This feedback mechanism enables automatic categorization by checking whether the round-trip mapping preserves category assignments, eliminating the need for user interaction while maintaining accuracy.
2Reliability
If N×M mapping is performed between different category hierarchies, then categorization consistency is improved, but the process becomes time consuming and complex
Solution Approach 1:
The system pre-defines mapping relationships between sender and recipient category hierarchies before actual object distribution occurs. These predefined mappings are stored and reused for multiple objects, eliminating the need to perform complex N×M mapping calculations repeatedly, thus reducing processing time while maintaining consistency.
Solution Approach 2:
The system verifies mapping convergence by applying the second mapping (recipient to sender) and checking whether it returns to the original sender category. This feedback mechanism ensures categorization consistency across different hierarchies while enabling automatic validation without requiring manual intervention or extensive processing time.
3Measurement precision
If bidirectional mappings are applied to ensure convergence, then mapping accuracy is improved, but system complexity increases
Solution Approach 1:
The system uses a universal mapping framework that handles both forward (sender to recipient) and backward (recipient to sender) mappings through the same bidirectional mechanism. This multi-functional approach improves mapping accuracy by ensuring consistency in both directions while avoiding the need for separate complex systems for each mapping direction.
Data Source
AI summary
An object may be categorized upon distribution of the object from a sender system to a recipient system. The object may be assigned to at least one recipient category in a recipient category hierarchy according to a first predefined mapping from a sender category hierarchy to the recipient category hierarchy. The object is initially assigned to a sender category in the sender category hierarchy. There is applied to the object a second predefined mapping from the recipient category hierarchy to the sender category hierarchy. It is determined whether the first and second predefined mappings converge. If the first and second predefined mappings do not converge, there may be executed a rule-based reassignment algorithm to make the first and second predefined mappings converge.