• DocumentCode
    3058417
  • Title

    Ontology-Based Knowledge Extraction for Relational Database Schema

  • Author

    Zhang, Guoqiang ; Jia, Suling

  • Author_Institution
    Sch. of Econ. & Manage., Beihang Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    22-24 May 2009
  • Firstpage
    585
  • Lastpage
    589
  • Abstract
    Translating large amounts of relational data into ontological knowledge can be a major challenge. Based on the DL-based formalization of E-R model and OWL DL ontology, this paper studies the method for translating E-R model to OWL DL-based ontology and constructs corresponding mapping relationship between them. A translation algorithm has been improved to realize the translation. Finally, a case is designed to verify the algorithm. Analysis indicates that the algorithm is accurate and effective; and it proposes a new method for construct ontology.
  • Keywords
    knowledge acquisition; knowledge representation languages; ontologies (artificial intelligence); relational databases; DL-based formalization; E-R model; OWL DL ontology; knowledge extraction; relational database; Algorithm design and analysis; Data mining; Humans; Knowledge management; Logic; OWL; Ontologies; Relational databases; Resource description framework; Semantic Web; E-R Schema; OWL DL; Schema Translation; ontology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Commerce and Security, 2009. ISECS '09. Second International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3643-9
  • Type

    conf

  • DOI
    10.1109/ISECS.2009.104
  • Filename
    5209855