RepRev: Mitigating the Negative Effects of Misreported Ratings


  • Yuan Liu Nanyang Technological University
  • Siyuan Liu Nanyang Technological University
  • Jie Zhang Nanyang Technological University
  • Hui Fang Nanyang Technological University
  • Han Yu Nanyang Technological University
  • Chunyan Miao Nanyang Technological University



Reputation models depend on the ratings provided by buyers togauge the reliability of sellers in multi-agent based e-commerce environment. However, there is no prevention forthe cases in which a buyer misjudges a seller, and provides a negative rating to an original satisfactory transaction. In this case,how should the seller get his reputation repaired andutility loss recovered? In this work, we propose a mechanism to mitigate the negativeeffect of the misreported ratings. It temporarily inflates the reputation of thevictim seller with a certain value for a period of time. This allows the seller to recover hisutility loss due to lost opportunities caused by the misreported ratings. Experiments demonstrate the necessity and effectiveness of the proposed mechanism.




How to Cite

Liu, Y., Liu, S., Zhang, J., Fang, H., Yu, H., & Miao, C. (2014). RepRev: Mitigating the Negative Effects of Misreported Ratings. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1).