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Combination of Similarity Measures in Ontology Matching Using the OWA Operator

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Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 265))

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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.

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Author information

Authors and Affiliations

  1. Institute AIFB, University of Karlsruhe, D-76128, Karlsruhe, Germany

    Qiu Ji, Peter Haase & Guilin Qi

Authors
  1. Qiu Ji
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  2. Peter Haase
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  3. Guilin Qi
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Editor information

Editors and Affiliations

  1. Machine Intelligence Institute , Iona College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

  2. Systems Research Institute , Polish Academy of Sciences, Ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  3. School of Information Technology , Deakin University, 221 Burwood Highway, 3125, Burwood, Victoria, Australia

    Gleb Beliakov

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Ji, Q., Haase, P., Qi, G. (2011). Combination of Similarity Measures in Ontology Matching Using the OWA Operator. In: Yager, R.R., Kacprzyk, J., Beliakov, G. (eds) Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice. Studies in Fuzziness and Soft Computing, vol 265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17910-5_15

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  • DOI: https://doi.org/10.1007/978-3-642-17910-5_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17909-9

  • Online ISBN: 978-3-642-17910-5

  • eBook Packages: EngineeringEngineering (R0)

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