The Method Based on Professionalism of Evaluator for Reliability Reputation Model
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.
Keywordsreputation model collaborative unfair rating professionalism
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- 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.Dellarocas, C.: The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms. Management Science 49 (2003)Google Scholar
- 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.Hoffman, K., et al.: A survey of Attack and Defense Techniques for Reputation Systems. ACM Computing Surveys 42 (2009)Google Scholar
- 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.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.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
- 11.MovieLens Data, http://www.cs.umc.edu/Research/GroupLens