• DocumentCode
    2028758
  • Title

    Detecting Ontology Mappings via Descriptive Statistical Methods

  • Author

    Todorov, Konstantin

  • Author_Institution
    Inst. of Cognitive Sci., Universtity of Osnabruck, Osnabruck
  • fYear
    2009
  • fDate
    24-28 May 2009
  • Firstpage
    177
  • Lastpage
    182
  • Abstract
    Instance-based ontology mapping comprises a collection of theoretical approaches and applications for identifying the implicit semantic similarities between two ontologies on the basis of the instances that populate their concepts. The current paper situates this general problem in the realm of finding mappings between the nodes of two different Web directories populated with text documents (the Web pages that they intend to organize). We propose a novel approach to detect potential concept mappings based on principle component analysis and discriminant analysis and introduce a resulting concept similarity measure. The procedure can be used as an independent concept mapping technique, or as a support to a concept similarity measure of other nature.
  • Keywords
    Internet; ontologies (artificial intelligence); principal component analysis; text analysis; Web directories; concept mappings; descriptive statistical methods; discriminant analysis; instance-based ontology mapping; principle component analysis; semantic similarities; text documents; Cognitive science; Independent component analysis; Ontologies; Performance evaluation; Statistical analysis; Taxonomy; Web and internet services; Web pages; Concept Similarity; Descriptive Statistics; Instance-based Ontology Mapping; Machine Learning; Ontologies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet and Web Applications and Services, 2009. ICIW '09. Fourth International Conference on
  • Conference_Location
    Venice/Mestre
  • Print_ISBN
    978-1-4244-3851-8
  • Electronic_ISBN
    978-0-7695-3613-2
  • Type

    conf

  • DOI
    10.1109/ICIW.2009.33
  • Filename
    5072516