Detecting unfair rating attacks in online rating systems

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 buye...

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Bibliographic Details
Main Author: Lee, Chin Hwee.
Other Authors: School of Computer Engineering
Format: Final Year Project (FYP)
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/10356/48491
Description
Summary: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.