• DocumentCode
    2158814
  • Title

    Building Semantic Web Services Automatically Based on PART

  • Author

    Wang, Lan ; Xu, Hong-Sheng

  • Author_Institution
    Acad. of Inf. Technol., Luoyang Normal Univ., Luoyang, China
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The Internet is the largest information repository. Most information retrieval systems are based on the premise that users know the keywords for searching subjects. Web services provide a suitable technical framework for making business processes accessible within enterprises and across enterprises, so that they have promoted a new paradigm of a business process which is called the service-oriented business process. The system then uses a Bayesian network to insert the terms and finish the complete hierarchy of the ontology. The feature of this ontology construction system includes that the PART architecture overcomes the lack of flexibility in clustering, while in the web page analysis, WordNet and Entropy deal with the lack of knowledge acquisition. Empirical results demonstrate that the new design help users with little domain knowledge obtain appropriate keywords.
  • Keywords
    ART neural nets; Web services; belief networks; knowledge acquisition; ontologies (artificial intelligence); semantic Web; Bayesian network; Internet; PART architecture; Web page analysis; WordNet; domain knowledge; entropy; information repository; information retrieval system; knowledge acquisition; ontology construction system; projective adaptive resonance theory; semantic Web service; service-oriented business process; Artificial neural networks; Bayesian methods; Construction industry; Ontologies; Resource description framework; Subspace constraints; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5325-2
  • Electronic_ISBN
    978-1-4244-5326-9
  • Type

    conf

  • DOI
    10.1109/ICMSS.2010.5576607
  • Filename
    5576607