Mediation Bridge Ontology Alignment Pattern Reusability
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Solution Overview
Problem
Existing ontology matching systems focus on automation and accuracy but fail to enhance the extendibility and reusability of ontologies, limiting their interoperability and adaptability in the semantic web.
Innovation Solution
The Mediation Bridge Ontology (MBO) apparatus employs object-oriented design patterns and strategy design patterns to provide an expressive alignment representation, enabling extendibility and reusability through a Pattern Relationship Model (PRM) that allows for the addition of new bridge algorithms and classes, thereby improving interoperability in knowledge management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing ontology matching systems focus on automation and accuracy, then alignment precision is improved, but extendibility and reusability of ontologies deteriorate
Solution Approach 1:
The ontology matching system is segmented into independent modules including a pattern repository, pattern selection component, and pattern application component. Each module performs a specific function (storing patterns, selecting patterns, applying patterns) that can be independently developed, maintained, and extended without affecting other parts of the system, thereby improving both precision and extendibility
Solution Approach 2:
The pattern repository stores reusable alignment patterns that can be applied across different ontology domains and matching scenarios. These universal patterns enable the system to handle diverse alignment tasks with a common set of mechanisms, improving reusability while maintaining alignment precision through proven pattern implementations
2Productivity
If existing ontology matching systems focus on automation, then matching efficiency is improved, but adaptability to new alignment scenarios deteriorates
Solution Approach 1:
The pattern selection component dynamically selects appropriate alignment patterns based on the characteristics of the input ontologies and the specific alignment task at hand. This dynamic adaptation allows the automated system to adjust its behavior to different scenarios while maintaining efficiency through algorithmic pattern selection rather than manual configuration
Solution Approach 2:
The pattern repository acts as an intermediary layer between the automated matching process and domain-specific requirements. New alignment scenarios can be accommodated by adding new patterns to the repository without modifying the core matching engine, enabling adaptability while preserving automated efficiency
Data Source
AI summary
An apparatus for processing Mediation Bridge Ontology (MBO) based on ontology alignment patterns. The apparatus includes an MBO strategy design pattern component to have a plurality of strategy design pattern classes, to request, from a Pattern Relationship Model (PRM) component, a PRM for execution of the plurality of strategy design pattern classes, to receive the requested PRM from the PRM component, to execute a strategy design pattern using the received PRM, to acquire alignment information from the executed strategy design pattern, and to store the acquired alignment information, an MBO mediation pattern component to add a new class to the MBO strategy design pattern component through an interface used for communicating with other objects, and the PRM component to have a plurality of PRMs, and, in response to a request from the MBO strategy design pattern component, to provide a PRM to the MBO strategy design pattern component.