Extended Tversky Similarity for Resolving Terminological Heterogeneities across Ontologies

  • DuyHoa Ngo
  • Zohra Bellahsene
  • Konstantin Todorov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8185)


We propose a novel method to compute similarity between cross-ontology concepts based on the amount of overlap of the information content of their labels. We extend Tversky’s similarity measure by using the information content of each term within an ontology label both for the similarity computation and for the weight assignment to tokens. The approach is suitable for handling compound labels. Our experiments showed that it outperforms existing terminological similarity measures for the ontology matching task.


Similarity Measure Weight Assignment Ontology Match Heterogeneity Type Concept Label 
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 2013

Authors and Affiliations

  • DuyHoa Ngo
    • 1
  • Zohra Bellahsene
    • 1
  • Konstantin Todorov
    • 1
  1. 1.LIRMMUniversity Montpellier 2France

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