• DocumentCode
    2285600
  • Title

    A Bayesian knowledge engineering framework for service management

  • Author

    Wang, Wei ; Wang, Hao ; Yang, Bo ; Liu, Liang ; Liu, Peini ; Zeng, Guosun

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai
  • fYear
    2008
  • fDate
    7-11 April 2008
  • Firstpage
    771
  • Lastpage
    774
  • Abstract
    Service management is becoming more and more important within the area of IT service management. How to efficiently manage and organize service in complicated IT environments with frequent changes is a challenging issue. Service and the related information from different sources are characterized as diverse, incomplete, heterogeneous, and geographically distributed. It is hard to consume these complicated data without knowledge assistant. To address this problem, a knowledge engineering framework is proposed to tackle the challenges of acquisition, structuring and refinement of structured knowledge regarding existing different unstructured information resource, and the Bayesian network is utilized as the knowledge model. This framework can be successfully applied on key tasks in service management, such as problem determination and change impact analysis. And a real example of Cisco VoIP system is introduced to show the usefulness of this method.
  • Keywords
    Internet; belief networks; Bayesian knowledge engineering framework; Bayesian network; change impact analysis; problem determination; service management; unstructured information resource; Bayesian methods; Data mining; Engineering management; Environmental management; Information resources; Knowledge engineering; Knowledge management; Power system management; Resource management; Technology management; Bayesian networks; change impact analysis; knowledge engineering; problem determination; service management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Network Operations and Management Symposium, 2008. NOMS 2008. IEEE
  • Conference_Location
    Salvador, Bahia
  • ISSN
    1542-1201
  • Print_ISBN
    978-1-4244-2065-0
  • Electronic_ISBN
    1542-1201
  • Type

    conf

  • DOI
    10.1109/NOMS.2008.4575210
  • Filename
    4575210