• DocumentCode
    2074003
  • Title

    CAOWL-SAI: Context aware OWL based semantic association inference

  • Author

    Nazir, Saqib ; Afzal, Muhammad Tanvir ; Abdul Qadir, Muhammad ; Maurer, Hermann

  • Author_Institution
    Centre for Distrib. & Semantic Comput., Mohammad Ali Jinnah Univ., Islamabad, Pakistan
  • fYear
    2010
  • fDate
    16-18 Aug. 2010
  • Firstpage
    746
  • Lastpage
    751
  • Abstract
    Semantic Web unleashed a new era of data processing by enabling machines to understand the semantics of data. This semantic expression is achieved by formal representation of knowledge in data models such as RDF or OWL. The RDF and OWL data model can be envisioned as graph data models. The discovery of implicit relationships (termed as semantic associations) between entities in RDF graph had been the focus of research from quite some time now. The semantic associations are found using different path associations between entities in a RDF graph. This paper, however, exploits OWL constructs in an intelligent way to mine implicit relationships between semantic entities. The discovered relationships may not be found directly using RDF model. We employed our techniques on the available datasets of University ontology benchmark.
  • Keywords
    formal specification; inference mechanisms; ontologies (artificial intelligence); semantic Web; ubiquitous computing; CAOWL-SAI; OWL data model; context aware OWL based semantic association inference; data processing; formal representation; graph data models; semantic Web; semantic associations; Data models; OWL; Ontologies; Resource description framework; Search engines; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networked Computing and Advanced Information Management (NCM), 2010 Sixth International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-7671-8
  • Electronic_ISBN
    978-89-88678-26-8
  • Type

    conf

  • Filename
    5572156