Matching large scale ontology effectively

Authors:
Zongjiang Wang;Yinglin Wang;Shensheng Zhang;Ge Shen;Tao Du
Affiliations:
Dept of Computer Science, Shanghai Jiaotong University, China;Dept of Computer Science, Shanghai Jiaotong University, China;Dept of Computer Science, Shanghai Jiaotong University, China;Dept of Computer Science, Shanghai Jiaotong University, China;Dept of Computer Science, Shanghai Jiaotong University, China
Venue:
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Year:
2006

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Abstract

Ontology matching has played a great role in many well-known applications It can identify the elements corresponding to each other At present, with the rapid development of ontology applications, domain ontologies became very large in scale Solving large scale ontology matching problems is beyond the reach of the existing matching methods To improve this situation a modularization-based approach (called MOM) was proposed in this paper It tries to decompose a large matching problem into several smaller ones and use a method to reduce the complexity dramatically Several large and complex ontologies have been chosen and tested to verify this approach The results show that the MOM method can significantly reduce the time cost while keeping the high matching accuracy.