YAM++ : A Multi-strategy Based Approach for Ontology Matching Task

نویسندگان

  • DuyHoa Ngo
  • Zohra Bellahsene
چکیده

In this paper, we present the capability of our ontology matching tool YAM++. We show that YAM++ is able to discover mappings between entities of given two ontologies by using machine learning approach. Besides, we also demonstrate that if the training data are not available, YAM++ can discover mappings by using information retrieval techniques. Finally, we show that YAM++ is able to deal with multi-lingual ontologies matching problem.

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تاریخ انتشار 2012