• DocumentCode
    2441131
  • Title

    Semantic Web-based Context-aware Service Selection in Task-computing

  • Author

    Huang, Runcai ; Zhuang, Yiwen ; Zhou, Jiliang ; Cao, Qiying

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Donghua Univ., Shanghai
  • fYear
    2008
  • fDate
    27-28 Dec. 2008
  • Firstpage
    97
  • Lastpage
    101
  • Abstract
    The hierarchy of task-computing and the decomposition strategy of complex task are analyzed according to the characteristics of task-computing in pervasive environment. The architecture relies on the semantic representation of service and content, however, the semantic representation is based on shared ontology. It can not only improve the accuracy and recall, but also realize the functions such as knowledge sharing, capability-based search, autonomous reasoning and semantic matchmaking. Thus, a dynamic semantic Web-based context aware service selection mechanism is proposed to filter and rank the matching services according to their dynamic context in order to optimize the discovery process and save the time and effort of users. In addition, the selection mechanism can be used to discover the useful static and dynamic context information to provide the most suitable and relative services for users.
  • Keywords
    Web services; ontologies (artificial intelligence); semantic Web; ubiquitous computing; autonomous reasoning; capability-based search; knowledge sharing; pervasive environment; semantic Web-based context-aware service selection; semantic matchmaking; semantic representation; task-computing; Computer architecture; Context awareness; Context modeling; Context-aware services; Educational institutions; Matched filters; Middleware; Ontologies; Pervasive computing; Semantic Web; Context-Aware; Semantic Web-Based; Service Selection; Task-Computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Simulation and Optimization, 2008. WMSO '08. International Workshop on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-0-7695-3484-8
  • Type

    conf

  • DOI
    10.1109/WMSO.2008.10
  • Filename
    4756965