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Ontology Matching Using TF/IDF Measure with Synonym Recognition

  • Marko Gulić
  • Ivan Magdalenić
  • Boris Vrdoljak
Part of the Communications in Computer and Information Science book series (CCIS, volume 403)

Abstract

Ontology matching is an important process for integration of heterogeneous data sources. A large number of different matchers for comparing ontologies exist. They can be classified into element-level and structure-level matchers. The element-level matchers compare entities ignoring their relations with other entities, while the structure-level matchers consider these relations. The TF/IDF (term frequency / inverse document frequency) measure is useful for specifying key terms weights in documents. In our matching system we use the TF/IDF measure for comparing documents that store data about ontology entities. However, the TF/IDF does not take synonyms into account, and it may occur that the terms that describe two entities the best are synonyms. In this paper we propose a matcher that combines the TF/IDF measure with synonym recognition when determining key term weights, in order to improve the results of ontology matching. Evaluation of the matcher is performed on case study examples.

Keywords

ontology matching TF/IDF synonym recognition ontology integration 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Marko Gulić
    • 1
  • Ivan Magdalenić
    • 2
  • Boris Vrdoljak
    • 3
  1. 1.Faculty of Maritime StudiesUniversity of RijekaRijekaCroatia
  2. 2.Faculty of Organization and InformaticsUniversity of ZagrebVaraždinCroatia
  3. 3.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia

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