• DocumentCode
    1670621
  • Title

    An Artificial Neural Network for Predicting Service Rating in the Presence of Rating Manipulation

  • Author

    Ping Zhao ; Xinfeng Ye

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
  • fYear
    2015
  • Firstpage
    608
  • Lastpage
    615
  • Abstract
    Accurately predicting a user´s rating to a service is a challenging task in the presence of malicious users that manipulate the ratings to services. Many existing service rating systems lack the ability that counter the manipulation of rating systems. This paper proposed an artificial neural network (ANN) based service rating scheme that counters the manipulation of service ratings. The scheme takes into account of both similarity-based rating and the ratings given by representative users when predicting a user´s rating to a service. Some experiments were carried out to compare the prediction accuracy of the proposed scheme with a well-known existing scheme WSRec [26]. The results show that the proposed scheme provides more accurate rating predictions in the presence of a large amount of malicious users.
  • Keywords
    Web services; neural nets; recommender systems; Web service; artificial neural network; service rating manipulation; service rating prediction; service recommendation; similarity-based rating; Accuracy; Artificial neural networks; Collaboration; Filtering; Neurons; Radiation detectors; Training; artificial neural network; service recommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Computing (SCC), 2015 IEEE International Conference on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-7280-0
  • Type

    conf

  • DOI
    10.1109/SCC.2015.88
  • Filename
    7207406