Detecting unfair rating attacks in online rating systems
In this project, you will be learning some classic algorithms for detecting unfair rating attacks in online rating systems. After this, it is expected for you to design and develop an algorithm of your own that will have better performance in detecting unfair ratings. (1.148Mb)
Lee, Chin Hwee.
Date of Issue2012
School of Computer Engineering
Centre for Computational Intelligence
If you ever buy thing online from an unknown seller, the seller’s rating information that is given to you, how certain are you to trust the seller? The seller’s rating that you had saw on the internet may or may not be the actual reflection of the seller trustworthiness. In order to help buyers with their purchasing decision, this has given research community to work on the effectiveness in detecting unfair rating on the online system. In this report, it will discuss two existing detecting unfair rating models which are BRS and TRAVOS. To further help the researcher in these areas to evaluate the effectiveness of the detecting models, it will also be discussed on the development of a marketplace simulation where researcher can run a virtual marketplace simulation where buyers and sellers can do transactions.
DRNTU::Engineering::Computer science and engineering::Information systems
Final Year Project (FYP)
Nanyang Technological University