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Reputation management systems are used to quantify trust, based on some reputation metrics. Anonymity is an important requirement in these systems, since most individuals expect that they will not be profiled by participating in the feedback process. Anonymous Reputation management (ARM) systems allow individuals to submit their feedback anonymously. However, this solves part of the problem. Anonymous ratings by one individual can be linked to each other. This enables the system to easily build a profile of that individual. Data mining techniques can use the profile to re-identify that individual. We call this the linkability problem. This paper presents an anonymous reputation management system that avoids the linkability problem. 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