The Method Based on Professionalism of Evaluator for Reliability Reputation Model

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 181)


Along with the growth of online environment, interest in reputation system has grown bigger. As a result, the system was attacked by malicious users. However, the system is used by various users, so that the unfair rating problem is classified as difficult to be solved. This paper proposed the method based on professionalism of evaluator. In addition, how robustly the proposed method performs is compared by experiments in the situation of collaborative unfair rating that ignores the majority role, which has been the prerequisite in many studies.


reputation model collaborative unfair rating professionalism 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Josang, A., et al.: A survey of trust and reputation systems for online service provision. Decision Support Systems 43, 618–644 (2007)CrossRefGoogle Scholar
  2. 2.
    Yang, Y., et al.: Defending Online Reputation Systems againgst Collaborative Unfair Raters Through Signal Modeling and Trust. In: Proceedings of the 2009 ACM Symposium on Applied Computing (2009)Google Scholar
  3. 3.
    Dellarocas, C.: The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms. Management Science 49 (2003)Google Scholar
  4. 4.
    Josang, A., Golbeck, J.: Challenges for Robust Trust and Reputation System. In: 5th International Workshop on Security and Trust Management, STM 2009 (2009)Google Scholar
  5. 5.
    Hoffman, K., et al.: A survey of Attack and Defense Techniques for Reputation Systems. ACM Computing Surveys 42 (2009)Google Scholar
  6. 6.
    Fouss, F., et al.: A probabilistic reputation model based on transaction ratings. Information Sciences 180, 2095–2123 (2010)CrossRefGoogle Scholar
  7. 7.
    Whitby, A., et al.: Filtering Out Unfair Rating in Baysian Reputation Systems. In: The Third International Joint Conference on Autonomous Agenst Systems, pp. 106–117 (2004)Google Scholar
  8. 8.
    Jøsang, A., Ismail, R.: The beta reputation system. In: Proceedings of the 15th Bled Electronic Commerce Conference, vol. 160, pp. 324–337 (2002)Google Scholar
  9. 9.
    Dellarocas, C.: Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior. In: Proceedings of the 2nd ACM Conference on Electronic Commerce, pp. 150–157 (2000)Google Scholar
  10. 10.
    Weng, J., Miao, C.Y., Goh, A.: Protecting Online Rating Systems from Unfair Ratings. In: Katsikas, S.K., López, J., Pernul, G. (eds.) TrustBus 2005. LNCS, vol. 3592, pp. 50–59. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringChung-Ang UniversitySeoulKorea
  2. 2.NTIS CenterKorea Institute of Science and Technology InformationDaejeonKorea

Personalised recommendations