Effective large scale ontology mapping

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:
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
Year:
2006

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Abstract

Ontology mapping is the key point to reach interoperability over ontologies. It can identify the elements corresponding to each other. With the rapid development of ontology applications, domain ontologies became very large in scale. Dealing with the large scale ontology mapping problems is beyond the reach of the existing algorithms. To improve this situation a modularization-oriented approach (called MOM) was proposed in this paper. This approach tries to decompose a large mapping 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. Experimental results indicate that the MOM method can significantly reduce the time cost while keeping the high mapping accuracy.