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Matching Large Scale Ontology Effectively

  • Zongjiang Wang
  • Yinglin Wang
  • Shensheng Zhang
  • Ge Shen
  • Tao Du
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4185)

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.

Keywords

Module Match Ontology Match Lexical Similarity Large Ontology Complex Ontology 
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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