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Effective Large Scale Ontology Mapping

  • Zongjiang Wang
  • Yinglin Wang
  • Shensheng Zhang
  • Ge Shen
  • Tao Du
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4092)

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.

Keywords

Bipartite Graph Graph Match Module Match Ontology Mapping Lexical Similarity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zongjiang Wang
    • 1
  • Yinglin Wang
    • 1
  • Shensheng Zhang
    • 1
  • Ge Shen
    • 1
  • Tao Du
    • 1
  1. 1.Dept. of Computer ScienceShanghai Jiaotong UniversityChina

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