• DocumentCode
    2338150
  • Title

    Automatic learning ontology from relational schema

  • Author

    Lu Yiqing ; Liu Lu ; Li Chen

  • Author_Institution
    Sch. of Inf. Manage., Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • fYear
    2012
  • fDate
    3-5 June 2012
  • Firstpage
    592
  • Lastpage
    595
  • Abstract
    In order to knowledge understanding and communication between different areas, knowledge sharing and coordination require a general conception framework of enterprise knowledge expression and communication, and form shared concept protocol in supply chain. There´re numerous useful history data in existing database of enterprise, and actually relational database contains concept model of related areas. This paper proposes 11 mapping rules to convert relational database schema to ontology. Several actual cases are present to explain these mapping rules, and comparison to some other existing methods is also discussed at the end of this paper.
  • Keywords
    learning (artificial intelligence); ontologies (artificial intelligence); protocols; relational databases; supply chain management; automatic learning; concept model; enterprise database; enterprise knowledge expression; form shared concept protocol; general conception framework; knowledge sharing; mapping rule; ontology; relational database schema; supply chain; Robots; Ontology; Ontology construction; Ontology learning; Relational schema;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Applications (ISRA), 2012 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4673-2205-8
  • Type

    conf

  • DOI
    10.1109/ISRA.2012.6219258
  • Filename
    6219258