• DocumentCode
    3127494
  • Title

    Personalized QoS Prediction forWeb Services via Collaborative Filtering

  • Author

    Shao, Lingshuang ; Zhang, Jing ; Wei, Yong ; Zhao, Junfeng ; Xie, Bing ; Mei, Hong

  • Author_Institution
    Peking Univ., Beijing
  • fYear
    2007
  • fDate
    9-13 July 2007
  • Firstpage
    439
  • Lastpage
    446
  • Abstract
    Many researchers propose that, not only functional but also non-functional properties, also known as quality of service (QoS), should be taken into consideration when consumers select services. Consumers need to make prediction on quality of unused web services before selecting. Usually, this prediction is based on other consumers´ experiences. Being aware of different QoS experiences of consumers, this paper proposes a collaborative filtering based approach to making similarity mining and prediction from consumers´ experiences. Experimental results demonstrate that this approach can make significant improvement on the effectiveness of QoS prediction for web services.
  • Keywords
    Web services; data mining; groupware; quality of service; Web services; collaborative filtering; personalized QoS prediction; quality of service; similarity mining; Availability; Collaboration; Collaborative software; Delay; Information filtering; Information filters; Quality of service; Software quality; Web and internet services; Web services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Services, 2007. ICWS 2007. IEEE International Conference on
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    0-7695-2924-0
  • Type

    conf

  • DOI
    10.1109/ICWS.2007.140
  • Filename
    4279629