Schema Matching Optimization via Incidence Graph Rewriting
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Solution Overview
Problem
Current schema matching systems face performance issues when handling large schemas, leading to time-consuming and error-prone tasks due to their combinatorial complexity and inefficiency, especially when multiple matchers are applied, resulting in suboptimal performance and quality of matching results.
Innovation Solution
A rewrite-based optimization technique is introduced, utilizing filter-based rewrite rules and a modeling tool to improve the performance of schema matching processes by pruning unnecessary comparisons and optimizing the execution order of matchers, which is applicable to various matching processes and does not compromise the quality of results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple matchers are applied to improve matching quality, then the quality of mapping results is improved, but the execution time increases significantly due to combinatorial complexity
Solution Approach 1:
The patent divides the matching process into hierarchical levels (element level, structure level, instance level) and applies different matchers at each level. This segmentation allows the system to use simpler, faster matchers at the element level and reserve more computationally intensive matchers for later levels, thereby maintaining matching quality while reducing overall execution time.
Solution Approach 2:
The patent implements preliminary filtering and preprocessing steps before applying full matching algorithms. By performing initial assessments and eliminating obviously non-matching elements early in the process, the system reduces the search space for subsequent matchers, significantly decreasing execution time while preserving the ability to identify high-quality matches.
2Reliability
If comprehensive matching algorithms are used to ensure accurate mappings, then the reliability of results is improved, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic matcher selection mechanism that adapts the complexity and type of matchers used based on the specific characteristics of the schemas being matched. The system can dynamically adjust the matching strategy, using simpler approaches when sufficient and more comprehensive algorithms only when necessary, thereby maintaining reliability while managing system complexity.
Solution Approach 2:
The patent introduces intermediary components such as filtering layers, preprocessing modules, and result aggregation mechanisms that mediate between the various matchers and the final output. These intermediaries organize the complex interactions between multiple matchers, making the overall system more manageable and maintainable while preserving mapping accuracy.
3Productivity
If element level techniques are used for faster execution, then the processing speed is improved, but the matching precision deteriorates compared to structure-based approaches
Solution Approach 1:
The patent segments the matching process into multiple levels, applying element level techniques at the first level for rapid initial matching and structure-based approaches at subsequent levels for refinement. This hierarchical segmentation allows the system to benefit from the speed of element level techniques while ultimately achieving the precision of structure-based methods through multi-level processing.
Solution Approach 2:
The patent implements a continuous multi-level matching process where the output of one level serves as input to the next level. Rather than performing a single matching operation, the system continuously refines results through multiple levels of processing, maintaining the speed advantage of element level techniques while progressively improving precision through structure-based refinement.
Data Source
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AI summary
In one embodiment the present invention includes a computer-implemented method of improving performance of schema matching. The method includes storing a matching topology that maps a first data structure to a second data structure. The method further includes identifying a first portion of the matching topology that is a candidate for improvement as determined according to an incidence graph. The method further includes rewriting the first portion of the matching topology with a second portion according to the incidence graph.