Data Exchange System with Multi-Level Rule Matching
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Solution Overview
Problem
Data exchange systems face interruptions due to unmatched mapping between different data standards, leading to failed data exchange processes, as various applications were developed for different purposes and follow distinct data standards, requiring conversion to a unified standard.
Innovation Solution
A data exchange method and apparatus that determine if each data range needs conversion, match codes and name descriptions with a preset matching rule, perform range conversion upon successful matching, mark ranges with failed matching, and store both converted and marked ranges in a database, allowing for manual matching and rule modifications to facilitate seamless data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data exchange systems align source data range set with standard range set one by one, then data exchange can be carried out, but the process is complex and time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-establishing multiple matching rules (general standard mapping rules, custom mapping rules, attribute mapping rules) before data exchange occurs. When data needs conversion, the system checks against these pre-prepared rules rather than creating alignments on-demand, significantly reducing the time and complexity of the data exchange process
Solution Approach 2:
The matching rule system is segmented into multiple hierarchical levels: general standard mapping rules for common cases, custom mapping rules for specific applications, and attribute mapping rules for detailed properties. This segmentation allows the system to handle different data conversion scenarios efficiently without requiring a single complex alignment process
2Reliability
If unmatched mapping occurs during data exchange, then the interactive process is interrupted, but this ensures data accuracy
Solution Approach 1:
The system introduces an intermediary mechanism - the multi-level matching rule system - that mediates between source data and standard range sets. When direct matching fails, the system can apply alternative matching rules or partial matching strategies rather than completely interrupting the process, maintaining both reliability and throughput
Solution Approach 2:
The system applies partial matching when complete matching is not achievable. Instead of requiring 100% exact matches that would interrupt the process, the system performs partial matching to convert what can be converted and handles remaining data through alternative rules, ensuring continuous data exchange while maintaining accuracy where possible
Data Source
AI summary
The disclosure relates to a data exchange method and apparatus, a readable storage medium, and a data exchange system. The method includes: determining whether each range in received data to be converted needs range conversion; in response to determining a range needs range conversion, acquiring a code and a name description of the range to be converted, and matching the code and the name description of the range to be converted with a preset matching rule; in response to a successful matching, performing range conversion on the range to be converted; in response to a failed matching, marking the range to be converted of which matching fails; and storing a converted range in a database, and storing a marked range in the database; and storing each range in the data to be converted in the database, to complete a data exchange process.