Reputation systems are typically based on ratings given by the users. When there are no mechanisms in place to detect collusion and deception, combining user testimonies as such to form a provider's reputation may not give an accurate assessment, especially if the context of the ratings is not known. Moreover, such systems are vulnerable to manipulations by malicious users. It is important to identify the rationale behind the ratings so that similar ratings (or ratings pertaining to a context) can be aggregated to obtain a reputation value meaningful in that context. This paper proposes a fuzzy approach to analyze user rating behavior to infer the rationale for ratings in a web services environment.
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