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Combination of Similarity Measures in Ontology Matching Using the OWA Operator

  • Qiu Ji
  • Peter Haase
  • Guilin Qi
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 265)

Abstract

In this paper, we provide a novel solution for ontology matching by using the ordered weighted average (OWA) operator to aggregate multiple values obtained from different similarity measures. We have implemented the solution in the ontology matching system FOAM. Using the similarity measures in FOAM, we analyze the way to choose different OWA operators and compare our system with others.

Keywords

Similarity Measure Machine Learning Technique Aggregation Operator Similarity Aggregation Ontology Match 
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 2011

Authors and Affiliations

  • Qiu Ji
    • 1
  • Peter Haase
    • 1
  • Guilin Qi
    • 1
  1. 1.Institute AIFBUniversity of KarlsruheKarlsruheGermany

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